Health and fitness management system

ABSTRACT

A health and fitness management system is provided that has a health and fitness application operating, e.g., on a smart phone, that can wirelessly communicate with an activity module worn on the user which has a motion sensor, e.g., an accelerometer. The application accepts food and weight inputs (e.g., from the smart phone) and user activity units (e.g., from the activity unit) and develops a user intrinsic metabolism. The application includes fitness arc and health quotient graphical indicators that guide the user on health and fitness activities.

CROSS-REFERENCES TO RELATED APPLICATIONS

The present application is a continuation-in-part of U.S. patentapplication Ser. No. 14/282,918, filed May 20, 2014, which is acontinuation-in-part of U.S. patent application Ser. No. 13/743,718,filed Jan. 17, 2013. The contents of each of these applications areincorporated herein by reference in their entirety.

FIELD OF THE INVENTION

The disclosed subject matter relates to a health management system, andto a system for managing the health and fitness of an individual.

BACKGROUND

Counting calories can be an inherently inaccurate process and cannot besuccessfully used to predict weight loss because food items and physicalactivity can be subject to wide variation, such as in relation to actualcalories ingested or burned, e.g., from individual to individual, overtime through life and even on a daily basis. Conventional weight lossprograms often require the user to track food intake, which may besubjective. For example, one person's serving size for a particular fooditem may be different from another person's serving size. Moreover,weighing and measuring food items may be difficult to accomplish, andalso difficult to do consistently over a course of a weight lossalgorithm. In addition, tracking calories burned may be difficult, asthe number of calories burned may vary from exercise to exercise andperson to person.

As can be seen, for these and other reasons, there is a need for a morecomprehensive health management system that is simple to use (i.e., toinput food consumption and physical activity information), and that mayadapt to an individual's particular and often changing response tocertain food intake and exercise. Beneficially, such a system shouldalso output metabolically related health parameters such as weightgain/loss, food quality, fluids intake and condition, salt intake andlevels, percentage of vitamin rich foods, and, in addition, provide anoverall health and fitness measurement that can be simply and readilyunderstandable.

SUMMARY OF THE INVENTION

According to one aspect, the described invention provides a method forinstantaneously and continuously assessing real time energy balance forfitness management of the described invention comprises, in order: (a)collecting food intake information for actual or expected food intake ofa user over a specified period of time and contemporaneously convertingthe food intake information into food intake energy units for the firstperiod of time, wherein the food intake units are based on relativeenergy content of one food compared to another without relying onstandard caloric values; (b) collecting by a device activity informationfor actual or expected activity by the user over the specified period oftime and contemporaneously converting the activity information intoenergy units for the user for the first period of time, wherein thecollecting for actual activity is achieved by wireless transmission by amotion sensor and the motion sensor is a programmable accelerometer, thefunctional status of which is altered by: (i) programming independent ofa magnetic field; (ii) collecting deflections of the accelerometerduring the activity in various positions inside the engineeredenvironment such that it records motion associated with one type ofactivity while excluding movement characteristic of another form ofactivity; (iii) applying a multiplier to the accelerometer deflectionscollected in (ii) to assign a weighted value indicative of the level ofeffort exerted during the activity; (iv) saving deflections from eachtype of movement such that deflection counts are segregated by activitytype and determining the amount of relative energy expended by the userduring any given time period in the activity type; (v) transferringdeflection counts and relative energy expended to a device; and (vi)processing the deflection counts and relative energy expended fordisplay by the device; (c) instantaneously deriving, via a computingdevice, a calculated currently determined constant that reflectsefficiency, which is a rate at which the user extracts energy from thefood units that can be referenced against predicted and actual changesin weight, wherein the constant is a surrogate for intrinsic metabolicrate; (d) instantaneously calculating by an algorithm from thecalculated currently determined constant in (c) a predicted energybalance for the user, by: 1. calculating a ratio of an amount ofactivity units expected divided by an amount of activity observed; 2.calculating a ratio of an amount of food units expected divided by anamount of food units observed; 3. weighting the ratio in (a) against theratio in (b) according to goals of the user; and 4. modifying theweighted ratio in (iii) by a rate at which the user performs theactivity/work; (e) instantaneously predicting a change in weight fromthe predicted energy balance; and (f) determining fitness level of theuser based on the efficiency of energy consumption.

In one embodiment, of the method, the programming independent of amagnetic field is by wireless transmission from a device. In anotherembodiment, the wireless transmission is a Bluetooth™ signal. In anotherembodiment, the device is selected from the group consisting of a smartcell phone, a computer and a tablet. In another embodiment, the deviceis a smart cell phone. In another embodiment, the programmingindependent of a magnetic field is by buttons on an activity modulecomprising the programmable accelerometer.

In another embodiment, the change in weight is displayable either as anumeric weight or as a colored dot display system. In anotherembodiment, the colored dot display system comprises: (a) a red dotrepresenting weight gain other than muscle; (b) a green dot representingmuscle growth or weight loss; and (c) a yellow dot representing nochange in fat/muscle ratios.

In another embodiment, the deflection counts in (d) are segregated byactivity type in a processor. In another embodiment, the activity typeis a general activity type. In another embodiment, the activity typeconsists of activity monitoring modes selected from the group consistingof a travel activity mode and a sleep activity mode.

In another embodiment, the accelerometer is a triaxial accelerometer.

In another embodiment, when the type of activity is sleep, the methodfurther comprises a method for measuring quality of sleep comprising:(i) assigning a time period in which the user is going to bed; (ii)collecting deflections of the accelerometer during the assigned timeperiod of (i); (iii) transferring the deflection counts collected in(ii) corresponding to sleep activity to a device; (iv) ending the timeperiod assigned in (i); and (v) processing the deflection counts fordisplay by the device, wherein an increase in accelerometer deflectionsrecorded compared to an average of accelerometer deflections recorded isindicative of a sleep disorder. In another embodiment, the sleepdisorder is selected from the group consisting of sleep apnea, insomniaand restless leg syndrome. In another embodiment, the sleep disorder issleep apnea.

In another embodiment, when the type of activity is sleep, the methodfurther comprises a method for determining an increased physiologicalbenefit during sleep comprising: (i) assigning a time period in whichthe user is going to bed; (ii) collecting deflections of theaccelerometer during the assigned time period of (i); (iii) transferringthe deflection counts collected in (ii) corresponding to sleep activityto a device; (iv) ending the time period assigned in (i); and (v)processing the deflection counts for display by the device, wherein nochange or a decrease in accelerometer deflections recorded compared toan average of accelerometer deflections recorded is indicative of anincreased physiological benefit during sleep. In another embodiment, theincreased physiological benefit is an increase in interstitial space inbrain. In another embodiment, the increased physiological benefit is anincrease in convective exchange of cerebrospinal fluid (CSF) andinterstitial fluid (ISF) in brain. In another embodiment, the increasedphysiological benefit is an increased rate of clearance from brain of aprotein linked to neurodegenerative disease. In another embodiment, theprotein is selected from the group consisting of β-amyloid (Aβ),α-synuclein and tau.

In another embodiment, the information used to determine weight gainother than muscle, muscle growth or weight loss, or no change infat/muscle ratios, is integrated into multiple parameters that form ahealth quotient displayed by the device as a single point on a scaleranging from fit to healthy to unhealthy to at risk.

According to another aspect, the described invention provides a methodfor instantaneously and continuously assessing real time energy balancefor fitness management comprising, in order: (a) collecting food intakeinformation for actual or expected food intake of a user over aspecified period of time and contemporaneously converting the foodintake information into food intake energy units for the first period oftime, wherein the food intake units are based on relative energy contentof one food compared to another without relying on standard caloricvalues; (b) collecting by a device activity information for actual orexpected activity by the user over the specified period of time andcontemporaneously converting the activity information into energy unitsfor the user for the first period of time, wherein the collecting foractual activity is achieved by wireless transmission by a motion sensorand the motion sensor is a programmable accelerometer, the functionalstatus of which is altered by: (i) at least one moveable magneticencircling the programmable accelerometer; (ii) collecting deflectionsof the accelerometer during the activity in various positions inside theengineered environment such that it records motion associated with onetype of activity while excluding movement characteristic of another formof activity; (iii) applying a multiplier to the accelerometerdeflections collected in (ii) to assign a weighted value indicative ofthe level of effort exerted during the activity; (iv) saving deflectionsfrom each type of movement such that deflection counts are segregated byactivity type and determining the amount of relative energy expended bythe user during any given time period in the activity type; (v)transferring deflection counts and relative energy expended to a device;and (vi) processing the deflection counts and relative energy expendedfor display by the device; (c) instantaneously deriving, via a computingdevice, a calculated currently determined constant that reflectsefficiency, which is a rate at which the user extracts energy from thefood units that can be referenced against predicted and actual changesin weight, wherein the constant is a surrogate for intrinsic metabolicrate; (d) instantaneously calculating by an algorithm from thecalculated currently determined constant in (c) a predicted energybalance for the user, by: 1. calculating a ratio of an amount ofactivity units expected divided by an amount of activity observed; 2.calculating a ratio of an amount of food units expected divided by anamount of food units observed; 3. weighting the ratio in (a) against theratio in (b) according to goals of the user; and 4. modifying theweighted ratio in (3) by a rate at which the user performs theactivity/work (e) instantaneously predicting a change in weight from thepredicted energy balance; and (f) determining fitness level of the userbased on the efficiency of energy consumption.

In one embodiment of the method, the change in weight is displayableeither as a numeric weight or as a colored dot display system. Inanother embodiment, the colored dot display system comprises: (a) a reddot representing weight gain other than muscle; (b) a green dotrepresenting muscle growth or weight loss; and (c) a yellow dotrepresenting no change in fat/muscle ratios.

In another embodiment, the deflection counts in (iv) are segregated byactivity type in a processor. In another embodiment, movement of the atleast one moveable magnet around the programmable accelerometerinitiates a programming change to alter the functional status of theaccelerometer into activity monitoring modes. In another embodiment, theactivity monitoring modes are selected from the group consisting of astandard mode (S), a running/jogging mode (A+), a bicycle mode (A), aweight lifting/resistance training/yoga mode (W+), an aerobic-based gymequipment mode (W) and a sleet activity mode. In another embodiment, thestandard mode (S) comprises routine daily activity. In anotherembodiment, the type of activity is selected from the group consistingof aerobic and non-aerobic. In another embodiment, the aerobic activityis selected from the group consisting of walking, jogging, running,biking, tennis, basketball, soccer, circuit training and ellipticaltraining. In another embodiment, the non-aerobic activity is selectedfrom the group consisting of weight lifting, yoga, Pilates, andresistance training.

In another embodiment, the accelerometer is a triaxial accelerometer.

In another embodiment, the at least one moveable magnet is a sphere. Inanother embodiment, the at least one moveable magnet is contained withinat least one tube. In another embodiment, the at least one tube islocated within a means for attaching the accelerometer to a user. Inanother embodiment, the at least one tube is located within a casing ofan activity module.

In another embodiment, when the type of activity is sleep, the methodfurther comprises a method for measuring quality of sleep comprising:(i) assigning a time period in which the user is going to bed; (ii)collecting deflections of the accelerometer during the assigned timeperiod of (i); (iii) transferring the deflection counts collected in(ii) corresponding to sleep activity to a device; (iv) ending the timeperiod assigned in (i); and (v) processing the deflection counts fordisplay by the device, wherein an increase in accelerometer deflectionsrecorded compared to an average of accelerometer deflections recorded isindicative of a sleep disorder. In another embodiment, the sleepdisorder is selected from the group consisting of sleep apnea, insomniaand restless leg syndrome. In another embodiment, the sleep disorder issleep apnea.

In another embodiment, when the type of activity is sleep, the methodfurther comprises a method for determining an increased physiologicalbenefit during sleep comprising: (i) assigning a time period in whichthe user is going to bed; (ii) collecting deflections of theaccelerometer during the assigned time period of (i); (iii) transferringthe deflection counts collected in (ii) corresponding to sleep activityto a device; (iv) ending the time period assigned in (i); and (v)processing the deflection counts for display by the device, wherein nochange or a decrease in accelerometer deflections recorded compared toan average of accelerometer deflections recorded is indicative of anincreased physiological benefit during sleep. In another embodiment, theincreased physiological benefit is an increase in interstitial space inbrain. In another embodiment, the increased physiological benefit is anincrease in convective exchange of cerebrospinal fluid (CSF) andinterstitial fluid (ISF) in brain. In another embodiment, the increasedphysiological benefit is an increased rate of clearance from brain of aprotein linked to neurodegenerative disease. In another embodiment, theprotein is selected from the group consisting of β-amyloid (Aβ),α-synuclein and tau. In another embodiment, the information used todetermine weight gain other than muscle, muscle growth or weight loss,or no change in fat/muscle ratios, is integrated into multipleparameters that form a health quotient displayed by the device as asingle point on a scale ranging from fit to healthy to unhealthy to atrisk.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the disclosed subject matter,reference can be made to the following detailed description of anexemplary embodiment considered in conjunction with the accompanyingdrawings, in which:

FIG. 1 is a schematic diagram in block diagram form of a health andfitness management system constructed in accordance with an exemplaryembodiment of the disclosed subject matter, the system having a healthand fitness application operating, e.g., on a smart phone, that canwirelessly communicate with an activity module;

FIG. 2 is an illustration of a food circle information screen on thesmart phone that can be provided by the application;

FIG. 3 is an illustration of a user profile input screen on the smartphone;

FIG. 4 is an illustration of a fluid and salt circle information screenon the smart phone;

FIG. 5 is an illustration of a weight related to fluid and saltinformation screen on the smart phone;

FIG. 6 is an illustration of a fitness arc information screen on thesmart phone;

FIG. 7A shows a user food choice input screen;

FIG. 7B shows an another user food choice input screen;

FIG. 7C shows an another user food choice input screen;

FIG. 8 is a user food portion input screen;

FIG. 9 is a user test results input screen;

FIG. 10 is a screen showing a graph of user test results over time;

FIG. 11 is a screen showing another graph of user test results overtime;

FIG. 12 is a screen showing a graphical circle that indicates theproportion of Vitamin K daily allotment consumed by the user during theday;

FIG. 13 is a schematic diagram of the health and fitness application;

FIG. 14A is a plane view of the activity module;

FIG. 14B is an side view of the activity module;

FIG. 15A is a plane view of a band which has a strap with a receptacleposition thereon, the band can be shown positioned adjacent to theactivity module;

FIG. 15B is a plane view of the band shown in FIG. 15A in which theactivity module can be shown installed in the receptacle;

FIG. 16 is a schematic drawing of the activity module;

FIG. 17 is a user activity estimation input screen;

FIG. 18 is a screen showing a command string for controlling theperformance of the activity module;

FIG. 19A is a screen showing a “deleted day” message;

FIG. 19B is a screen showing an “algorithm reset on this day” message.

FIG. 20 is a screen showing firmware commands;

FIG. 21 is a fitness arc information screen showing a fitness loss;

FIG. 22 is a recap information screen showing a fitness arc (top),percentages of good carbs, bad carbs, protein (Prot) and Fat consumed(middle) and health quotient (bottom);

FIG. 23 is a picture of a side view of a band for the activity modulewhich has a strap with a receptacle;

FIG. 24 is a side view illustration of a band for the activity modulewhich has a strap with a receptacle holding the activity module;

FIG. 25A is a picture of a top view of a band for the activity modulewhich has a strap with a receptacle;

FIG. 25B is a picture of a bottom view of a band for the activity modulewhich has a strap with a receptacle;

FIG. 26A is a picture of a top view of a receptacle;

FIG. 26B is a picture of a bottom view of a receptacle;

FIG. 27 is a picture of a top view of a band which has a strap with areceptacle holding an activity module;

FIG. 28 is an illustration of a fastening mechanism of a band;

FIG. 29 is a screen showing weightless fitness management programresults;

FIG. 30 is a screen showing results of the activity monitoring mode forsleep;

FIG. 31 is a user profile screen showing selection of an “Arc label”;

FIG. 32 is a screen showing training circles for muscle training (top)and cardio (bottom); and

FIG. 33 is a screen showing an “Activity” circle displaying a user'stotal activity goal for the day and an “Activity Contribution” bardisplaying the relative amounts of aerobic (60%) and muscle training(40%) performed to fill the activity circle.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

The described invention can be better understood from the followingdescription of exemplary embodiments, taken in conjunction with theaccompanying figures and drawings. It should be apparent to thoseskilled in the art that the described embodiments of the describedinvention provided herein are merely exemplary and illustrative and notlimiting.

DEFINITIONS

Various terms used throughout this specification shall have thedefinitions set out herein.

The phrase “count minimum” as used herein refers to the number ofdeflections a motion sensor, e.g., an accelerometer, must sequentiallycount before the motion sensor, e.g., accelerometer, begins to recorddeflections. For example, for a count minimum of 20, if an accelerometercounts 15 deflections followed by a silent period of no motion, theaccelerometer will not record the 15 deflections.

The phrase “detection time” as used herein refers to the number ofevents the motion sensor, e.g., accelerometer, is permitted to recordper unit time. The range of the detection time may be, for example, infractions of seconds.

The phrases “engineered magnetic environment” or “engineeredenvironment” as used interchangeably herein refer to a pre-specifiedposition/orientation of the activity module/motion sensor (i.e., theaccelerometer) within a magnetic field. In some embodiments, theposition/orientation of the activity module/motion sensor isfixed/static. In some embodiments, the position/orientation of theactivity module/motion sensor is dynamic. In some embodiments theposition/orientation of the activity module/motion sensor comprises bothfixed/static and dynamic components.

The phrase “general activity category” or “general activity ledger” asused herein refers to the number of accelerometer deflections that takeplace outside the magnetic field.

The phrase “health quotient” as used herein refers to the value assignedto an individual user that represents a measure of health and fitnessbased on the algorithm of the described invention. The algorithmincorporates, among others, activity amount, types of activity,direction of change in the amounts and types of activity, food amount,types of food, changes in the types of food consumed, the distributionof food intake throughout a day, the number of sleep deflections and thedirection in the number of sleep deflections per night, weight and thespeed of change in weight, the amount of salt consumed, the number andpercentage of vitamins consumed and the amount of fiber consumed. Once auser selects a fitness goal, a health quotient algorithm is calculatedfor the user. The user is placed on a continuum of the health quotientbar (e.g., fit, healthy, unhealthy, at risk) which changes over timebased on the algorithm.

The term “multiplier” as used herein refers to the number by which therecorded motion sensor (e.g., accelerometer) count is multiplied at theprocessor before being assigned to the algorithm in the activity circleof the activity module application.

The phrase “release time” as used herein refers to the amount of timebetween two sequential motion sensor (e.g., accelerometer) deflectionsthat is allowed to elapse before the second deflection is considered anew or separate event and thus not part of the same sequence.

The term “sensitivity” as used herein refers to the speed ofacceleration required for the motion sensor (e.g., accelerometer) todetect movement.

The disclosed subject matter provides a health management system thatincludes an application that employs readily identifiable icons tofacilitate the input of food consumption information, a motion sensor toautonomously facilitate the input of physical activity information, andthe direct input of weight information into the application. Theapplication utilizes the food consumption, physical activity, and weightinput information to formulate and periodically adjust a resting orintrinsic metabolism for the user. The system provides instantaneousfeedback on the relationship of food items and exercise to one's fitnesslevel, including one's weight. The system does not require the user tocount calories, either on the intake or expenditure side of the weightmanagement paradigm. Rather, the system employs icons and graphicdisplays, without units, to provide a user-friendly interface. Thehealth management system can also integrate weight, food intake andphysical activity and can learn the individual's unique response to eachelement to predict the direction of weight gain or loss.

In an embodiment, the system includes a digital device such as a smartcell phone or tablet device which, for example, may employ an Androidoperating system. The device runs a software application includingalgorithm code adapted to i) receive an input corresponding to thecalories consumed by the user via a graphical representation of the foodportion that can be graphically adjusted by the user, ii) receive aninput corresponding to physical activity of the user via wirelesstransmissions by a motion sensor worn by the user, and iii) receive aninput corresponding to weight of the user via direct input by the user.The application predicts the user's fitness level and intrinsicmetabolism based on the input corresponding to calories consumed and thecalculation of calories burned due to activity, and adjusts the user'sfitness level prediction based on historic measurements of the caloriesconsumed, the calories burned, and the weight of the user. Theapplication also uses the data to predict what can happen to the user'sweight based upon the real time assessment of caloric needs. Theapplication provides graphics which can be updated at predeterminedintervals, such as every ten minutes, to reveal fitness parametersincluding the user's daily overall energy balance.

There can be, by way of example, four components or parameters that canbe used by an algorithm in the system. Briefly, the components can becalories consumed, calories burned through activity (e.g., exercise),weight, and the calories necessary to maintain basic physiologicfunction or intrinsic metabolism. If three of these parameters can beknown, then the fourth can be derived via an energy balance calculation.Therefore, formulating the intrinsic metabolism requires registering thecalories consumed, and monitoring and assigning caloric value tophysical activities. The energy balance calculation is disclosed ingreater detail hereinafter.

FIG. 1 illustrates a health management system 10 (“the system”) whichcan be constructed in accordance with an exemplary embodiment of thedisclosed subject matter. The system 10 can include a health and fitnessapplication 12 (“the application”) and an activity module 14. Theapplication 12 can communicate wirelessly with the activity module 14,e.g., via Bluetooth™ or other ad hoc local wireless node transmission,e.g., over channels BT1 and BT2. The activity module 14 can be worn bythe user, for instance when he/she exercises, to measure and wirelesslytransmit activity units accumulated during exercise, to the application12. The application 12 can, by way of example, convert the activityunits into calories burned during exercise (i.e., in addition to thecalories burned by intrinsic metabolism).

Referring to FIG. 2, the application 12 can be adapted to run on adigital device D such as a smart phone, tablet computer, or conventionalpersonal computer, such as a desktop or laptop computer. In anembodiment, the digital device D may run a Smartphone based operatingsystem. Alternatively, the application 12 may be employed on astand-alone device such as a wrist-watch like device or other digitaldevice (not shown) that can be specifically adapted to provide thefunctionality described in the present patent application.

The application 12 can include a plurality of software algorithm codesfor displaying data, calculating data, receiving data and the like. Whenthe software can be run on the digital device D, buttons such as primaryinput buttons 16, 16 a-16 c and secondary input buttons 18, 18 a-18 cmay be displayed. The buttons 16, 16 a-16 c and secondary input buttons18, 18 a-18 c may be touch pad input buttons when the digital device Dincludes a touch screen. In another embodiment, a graphical userinterface, such as a mouse with a selection button(s) (not shown), e.g.,the right or left key selection button on the mouse, may be used tonavigate an icon about the screen of the digital device D and theselection button may be used to select one or more buttons 16, 16 a-16 cand secondary input buttons 18, 18 a-18 c, e.g., by clicking on suchbutton representations of the screen or icons or the like.

Selected buttons 16 b, 18 a may be highlighted on the screen. In thiscase, the primary input button 16 b for “balance” and the secondaryinput button 18 a for “food” may be selected. In an embodiment, thebutton 16 b for balance provides the following three secondary buttonoptions which can then be icons or button representations, e.g.,positioned at the bottom of the screen as illustrated in FIG. 2. Theoptions are briefly described below followed by more detaileddisclosures in the present patent application.

The Food Tab/Button:

As depicted on the screen of the digital device D as shown in FIG. 2 afood circle 20 can be used to represent an allowed daily amount of food,e.g., that can be necessary to maintain a current weight of the user. Itcan be color coded, e.g., filled with green color which can turn red,e.g., as the user adds more food than allowed. It can be understood thatcolors described herein can be depicted as fill-patterns in the figures.Although the color code for the fill-pattern can be shown on FIG. 2, thecode can remain the same for all figures in the present application. Itcan also be understood that any graphical element (e.g., food circle 20)that fills with the color red will also be accompanied by a message thatwill be displayed (not shown) which will described the impact of thatcolor change on the relevant physiologic function. The amount of foodrequired to fill the food circle 20 can be specific to each individualand can also vary with certain factors, such as the amount of activitythe user performs. For example, if the food circle (pie chart) 20 can bered or partly red, the user should be gaining weight for that day and inproportion to the amount of the food circle 20 that can be showing redas opposed to green. The user can change color back to green, e.g., bydoing more physical activity.

Fluid/Salt Tab or Button 18 b:

As depicted on the screen of the digital device D as shown in FIG. 4fluid and salt circles 26, 28, respectively can be used to indicate adaily 26 allotment amount in circle 26, which may be determined from anestimated daily fluid consumption goal, which may be input by the useron field 24 f, e.g., as depicted on a profile page 24 depicted in FIG.3, discussed in more detail below. Actual fluid consumption can then beinput by the user throughout the day. The salt circle 28 can fill, e.g.,as dietary choices can be made throughout the day. Green can then beused to represent that the user can be consuming or has consumed salt ina manner that can be, e.g., consistent with current dietaryrecommendations. In an embodiment, if the user exceeds recommended saltallowances as the day progresses, the color can progressively change,e.g., to yellow, as indicated by the no cross-hatching for red shown inFIG. 2 and then red as the user inputs his/her food consumed.

Weight Tab/Button 18 c:

As depicted on the screen of the digital device D as shown in FIG. 5,the device includes weight information, e.g., on a daily basis, andassociated proportional fluid 31A and salt information 31B. Greenindicates compliance with health and fitness guidelines, yellowindicates excess, and red indicates overly excessive (e.g., unhealthy)consumption. In an embodiment, previous weeks can be reviewed by tappingthe left return arrow 33 on the date bar to move for display on thescreen of the prior weeks and the right advance arrow 33 to move forwardin time back to the current week.

As disclosed in more detail below, the application 12 can convert iconicfood items input by the user into a numeric figure which, as an example,over time may be learned by the system, e.g., by derivation from ananalysis of previous food selections and their impact on weight whenalso, e.g., compared with the user's actual and historic activity leveland when referenced against the calculation of intrinsic metabolism bythe system 10. The intrinsic metabolism may, by way of example, be heldas a constant until it can be determined by the system 10 that thisvalue for intrinsic metabolism no longer correctly predicts thedirection/amount of weight gain or loss. At such time the system 10 mayrecalculate the value for intrinsic metabolism and retain it as thepresent constant, e.g., so that the instantaneous energy balance of theuser can be calculated and displayed on a user friendly and readilyidentifiable graphic, as can be shown, by way of example in a fitnessarc 34 in FIG. 6.

Referring back to FIG. 2, in an embodiment, graph 20, as illustrated asa circle graph, can be used to display allowed food intake and actualfood intake, respectively, for a given day. For example, circle graph 20may indicate that the user's total food intake for the given day can beless than the maximum prescribed, e.g. as indicated by the portion ofcircle graph 20 that can be white (no cross-hatching, e.g., indicatingthe food intake can be about 30% below recommended), or can be ontarget, e.g., if the green color increases to fill the entire circle(not shown in FIG. 2), or can be “excess,” e.g., by the portion that canbe in red, that is not shown on the circle graph 20, but can be imaginedas the white portion becoming green. This would then indicate, as anexample, that the food intake was about 30% in excess.

As noted above, the circle graph 20 can be, e.g., a proportionalrepresentation of the way in which the user's daily food consumption hasbeen distributed between the major food groups, and this can becalculated by the application 12. The circle graph 20 may show one colorfor food caloric intake (for example, a white background changing togreen as calories are consumed), the background color also showing thefood units remaining, which if consumed to the allowed amount can resultin the user reaching the pre-selected weight goal (the white colorremaining), and another color, e.g., red when caloric intake exceeds theallotted calories for the given time period. The graphic allowance forfood intake can be adjusted to the user's activity level each day, sothat, if the activity level increases above the expected, an adjustmentcan be made which can, e.g., allow more food to be entered before thefood circle 20 can be completely filled.

In an embodiment, the bar graphs 22 may be utilized to further breakdown various food intake categories into separate graphs. For example,carbohydrates (carbs) may be broken down into bar graphs on good and badcarbs 22 a, 22 b, respectively, and protein and fat may be displayed ongraphs 22 c, 22 d, respectively. Allotments (i.e. how much room therecan be to fill the graphs for each food type) depend on the diet whichcan be input by the user in field 24 g of the profile page 24 depicted,by way of example, in FIG. 3. If the user changes his/her diet, the barheights for each of the food groups can also change. The graphs 22 a-22d may be useful for persons on a low fat or a low carb diet. The graphs22 may be color coded, as noted above as an example. For example, thegood carb 22 a, the protein 22 c and fat 22 d graphs may be partly greenon a white background, to show that the daily allotment has not yet beenconsumed, but the bad carb 22 b graph may be changed to completely red,showing that the daily allotment has been exceeded, or as noted abovewith the circle graph of FIG. 2, may change to red on the greenbackground when and to the degree that excess bad carbohydrate intake isincreased above the recommended level. The percentages of food type canbe assigned by the application 12 so that the user only selects theiconic representation of the food item (i.e., during food consumptionestimation inputs, as discussed in more detail below), and theapplication 12 can then determine the percentages of each elemental foodtype (i.e., protein, fat, carbohydrate, as well as salt content) thatcan be contained therein.

The actual allowed amount of food type which can be permitted before thegraphs 22 a-22 d can completely fill in over the initial backgroundcolor and change color can be determined by the allowed food amount,which can be determined, e.g., by the application 12 and the diet typeselected by the user or health advisor, e.g., as input on a user profilescreen 24 shown in FIG. 3. More particularly, with reference to FIG. 3,in an embodiment, the user profile input screen 24 can be employed toinitially set up, as well as change, parameters such as Profile 24 a(user sex, type and frequency of exercise training, etc.), StartingWeight 24 b, Calories 24 c (daily consumption objective), Target Weight24 d, User Estimated Activity 24 e (estimate of number of user activityunits, as described below), Fluid Amount 24 f (amount of fluid desiredto be consumed daily, in ounces). The fluid amount may be determined,e.g., by the user's weight, but the targeted amount of fluid to beconsumed can be adjusted, by way of example, at the user's/healthadvisor's discretion. The color coding for fluid, in an example, may notattempt to target a minimum or maximum allowance, but may simply allowthe user to track the volume of fluid consumed. The target for saltconsumption may, e.g., track standard daily sodium contentrecommendations. In some cases, this may not be open to adjustment bythe user. The user profile input screen 24 can also include parameterssuch as Diet Choice 24 g, and an Instant Compare Option 24 h (which canallow instant input of activity units in the application 12, as opposedto an input in the application 12 that attempts to replicate normalmetabolic changes, e.g., every three hours, thus permitting the user togain instant access to the impact of his/her activity units).

In an embodiment, the system 10 normally can be employed using some orall of the features described in the present application in connectionwith the application 12, e.g., while operating in conjunction with theactivity module 14 (i.e., operating in a “combined mode”), or in a modein which all the features described herein in connection with theapplication 12 can be operating without inputs from the activity module14 (i.e., “the estimated mode”). The application 12 can be switched backand forth between the estimated mode and the combined mode on the userprofile input screen 24 by checking or unchecking ESTIMATED (not shownin FIG. 3). For example, the user may elect i) to not wear the activitymodule 14 at all during a particular day, ii) or to just wear it forexercise only on a particular day, in which instance the estimatedactivity can be entered just before beginning the exercise. The activityaccumulated by the activity module 14 can be downloaded after theexercise.

Referring to FIG. 4, in an embodiment, when secondary input button 18 b“fluid/salt” can be selected, the user can observe during the day his orher progress with fluid and salt intake, as it relates to the objectivesestablished in the user profile input (i.e., see FIGS. 3, 24 f and 24g). In an embodiment, the progress may be shown on fluid and saltcircles 26, 28, respectively. The fluid and salt circles 26, 28 may becolor coded to help reveal desired intake, current intake amountremaining or in excess of recommendation. The circle graphs 26, 28 mayalso be helpful, for example, in monitoring salt intake for users on asalt-restrictive diet. In addition, fluid/salt progress indicators canbe associated with weight on a weight summary screen 31 which can bedescribed below.

FIG. 5 illustrates a weight summary screen 31 listing the daily weighthistory and associated fluid and salt color coded indicator circles 31Aand 31B, respectively, for the current week. Each food item can beassigned a salt value and serve to fill the salt circle 28 as apercentage of food units calculated by the application 12, such that thehigher the percentage of the high salt foods, the fewer food units canbe needed to be consumed to fill the salt circle 28. The fluid circle 26depicted on FIG. 4 fills as liquids can be selected. The fluid and saltcircles 26, 28 or representations of them can populate the listing 31 tohelp the user analyze the effect of fluid and salt on weight.

Referring to FIG. 6, the results of the energy balance calculation canbe presented graphically on the digital device D screen, e.g., as agraphical fitness arc 34. The fitness arc 34 can be utilized to depict ameasurement of daily energy balance and provide a daily indicator offitness and health. In an embodiment, the accuracy of the fitness arc 34can be enhanced by the application 12. More particularly, theapplication 12 can, e.g., periodically recalculate the user's intrinsicmetabolism to provide an energy balance correction. Every person has aunique and changing metabolism such that consumption of similarquantities of food and similar amounts of activity can have differenteffects on the weight of the user, which weight can be utilized as afitness indicator. Thus, there can be a different amount of remainingenergy units available every day for storage as fat and thereforedifferent consequences to weight in different individuals. Thisdiscrepancy can occur even if activity and food consumption can beidentical. This constitutes the meaning of intrinsic metabolismaccording to the presently disclosed subject matter. These parameterscan be continuously varying, i.e., they can be constantly changing withresultant different effects on weight for any individual user. Theapplication 12, by monitoring its ability to predict weight based uponthe activity units and food intake input, can constantly vary theallowed food intake should the application fail to accurately predictthe change in the weight of the user. Thus, the continuous variable ofintrinsic metabolism can, as an example, constantly be adjusted tocorrect for changes in the rate of energy consumption as fitness levelschange or as food consumption and activity patterns change. By adjustingthe metabolism calculation the application 12 can, e.g., determinemodified food allowance(s) to match changes in activity.

The application 12 by way of example, can work without a requirementthat the food input from the user be accurately reflective of the actualcalorie content of food consumed. The application 12 only requires thatthe user have a reasonably similar pattern of icon use to describe foodintake. For example, a sandwich eaten on one day may be bigger orsmaller than the same eaten the day before, but the system does notrequire the user to actually reflect the absolute caloric contentconsumed. The algorithm can, by way of example, learn the way the userdescribes food and then assign a food unit value to each food component,e.g., contained within the sandwich, based upon an algorithm utilized bythe application 12. In this manner, any habitual over/under food portionestimation(s) by the user can be detected and compensated for, therebyfacilitating the application 12 in maintaining or reaching a user'starget weight goal as specified in the user's profile (see FIG. 3, 24d).

Continuing to refer to FIG. 6, when primary input button 16 a, “fitnessarc” can be selected, a color coded energy deficiency/energy excessfitness arc 34 can be displayed on the display screen of the digitaldevice D. In an embodiment, the fitness arc 34 can be formed in asemi-circular shape, where one side of the semi-circle can be an energydeficit portion 34 a (i.e., indicative of weight loss) and the otherside of the semi-circle can be an energy excess portion 34 b (i.e.,indicative of weight gain). In an embodiment, a red color may show whenthe energy deficit 34 a can be present for that particular moment of theday (e.g., within periodic updates, such as, 10 minute updates), and agreen color may show when the energy excess 34 b can be present for thatday. The portions 34 a, 34 b of the fitness arc 34 can change throughoutthe day, depending on the user's indicated physical activity andindicated food consumption. In an embodiment, coincident with the updateof the fitness arc 34, a fitness arc value 34 c can also be displayed.This value can represent the delta or change in fitness arc 34 unitswith each periodic, e.g., 10 minute interval, e.g., plus for an increasein energy excess (the body can be consuming energy through activity at ahigher rate than necessary based on indicated food intake and thecurrent intrinsic metabolism of the user) and negative for an increasein energy deficit (the body can be consuming energy through activity ata lower rate than necessary based on the indicated food intake and thecurrent intrinsic metabolism of the user). At the conclusion of eachday, the fitness arc 34 c final value can be displayed. It can also beunderstood that the value for the fitness arc can be normalized and thecolor coded indication on the arc 34 used to indicate the positive ornegative state of the energy consumption.

The fitness arc 34, therefore, can be used to visually inform the useras to the effect of the real time food consumption of the userreferenced against the real time analysis of the actual physicalactivities of the user. At any given point in the day, the actualactivity units and their impact on the fitness arc 34 can then bereferenced against expected or historic levels of activity for that sametime of the day. The fitness arc 34 displays can be adjusted based uponwhat can be expected and what has occurred. Activity units can bemeasured and assigned a value based upon the currently determined valuefor the calculated intrinsic metabolism of the user. The activity unit'svalue can be then used to calculate the energy balance that also canthen be used to predict weight gain or loss, even before the foodconsumption or activity can be carried out.

Thus, given the inherent variation between each individual's rate ofintrinsic metabolism and the manner in which he/she describes the foodwith the available icons, and/or activity input, each user can havedifferent food unit values assigned to the same indication for a fooditem(s). The effect of activity on the balance of energy can becalculated, not directly against the food unit intake but it can befirst processed, by the application 12, through a separate algorithm,e.g., imbedded in the calculation of the intrinsic metabolism. Thusneither food nor activity directly affects the energy balance or fitnessarc 34, but can be instead analyzed based upon their historic and/orlearned impact on intrinsic metabolism. The application 12 thus cancreate an ongoing user profile of intrinsic metabolism, activity, andfood choice/amount that can be unique to each user. In an embodiment,the various components of application 12 may be calculated periodically,e.g., at 10 minute intervals, although other intervals can be alsoapplicable. In an embodiment, it may take the application 12 about twoweeks to define and calculate the user's metabolic profile and assignthe values to his/her activity units and food intake units. It can beunderstood that such analysis can be further refined and adjusted by theselection of a target weight by the user. The algorithms, programs, orcalculations underlying the behavior of the fitness arc 34 are describedin greater detail below.

As disclosed above, the four components or parameters used by thealgorithms in the application 12 can be indicated food intake (and,thus, apparent calories consumed), indicated type and amount ofactivity, i.e., exercise (and thus, apparent calories burned throughactivity), weight, and finally the calories necessary to maintain basicphysiologic function, i.e., intrinsic metabolism. The application 12,therefore, can begin a monitoring process by assigning a value to eachof the four parameters and running a series of daily calculations todetermine the accuracy of the assigned values in relation to oneanother. The accuracy can be determined, by way of example, on theability for one set of assigned numbers to accurately predict theothers. Based on a weighted numerical coefficient of each data pointwhich can, e.g., vary at specified times of the day and week, thealgorithm can, e.g., choose three of the four definable parameters andthen calculate the fourth variable, e.g., for one, some or all of thevariables.

If the algorithm fails to predict the fourth value accurately, whereaccuracy can be defined in such a manner that, e.g., if the calculatedvariable can be reinserted into the application 12, the application 12accurately predicts the parameters that can be measured at that time,which can be seen as confirming the accuracy of the calculated variable,then new values may be assigned, e.g., to the other variables, and thecalculation redone until each variable accurately predicts the otherswhen inserted into the algorithm of the application 12. The variableschosen for analysis may also be seen and learned to vary at differenttimes of the day or week and the application 12 suitably varied tospecify that the value can have the greatest accuracy relative to theother values according to the learned/determined variability. Thisrecalculation may also include actual weight which can be directlymeasured.

The most complicated of the calculations may often be determined to bethat of the intrinsic metabolism for a given user. In this case, theremay be no direct measurement and thus the value can be, of necessity, aderived value, which may also vary from user to user and for a givenuser over time and in many cases according to one or more variables,e.g., daily, weekly, monthly, seasonally, time of day, exercise scheduleand the like. This changing variable for intrinsic metabolism can be,e.g., derived from the dynamic interplay of the measured/indicatedvariables, which can be, e.g., first referenced against, e.g., thepredicted value and/or actual value of each parameter. As data about theindividual user can be collected, the learned allowed variance betweenmeasured variables can be narrowed. The intrinsic metabolism can becalculated and held as a constant.

However, the intrinsic metabolism may be, e.g., held as a constant onlyfor a prescribed period and recalculated as metabolism for the userchanges. In other words, if three of the variables can be measured and arate of change in weight calculated, a constant can be calculated forthe intrinsic metabolism. The constant for intrinsic metabolismcurrently calculated can then be used to predict weight given theindicated activity and indicated food intake. Should the algorithm failto accurately predict weight given the indicated activity and foodintake for the user, then the constant for intrinsic metabolism can bechanged. When the constant for intrinsic metabolism can be found toperform adequately in the algorithm of the application 12, the algorithmcan maintain the use of the constant and predict, e.g., using changes ineither indicated activity or indicated food intake to predict acumulative impact on fitness, e.g., as measured by change or lackthereof in weight. The algorithms of the application 12 can then be usedto study the relationship between the two ongoing variables, indicatedactivity and indicated food intake, and combine the variationssimultaneously and contemporaneously to each other so that, as anexample, as one varies, the other can be determined even without thenecessity of direct and absolute measurement for the variable, i.e., insuch a way that if the user were to actually consume the enteredindicated food intake and/or were to actually perform theindicated/entered number of activity units, then the user's weight wouldremain unchanged. In other words, the algorithm for the application 12can adjust to inaccuracies in the indications of the food intake and/oractivity level, which, if consistently entered by the user and/ordetermined by the system 10 from inputs from the user or inputs from acomponent in the system 10 itself, can still determine a constant forintrinsic metabolism and other metabolic activity of the user so as toaccurately predict change in fitness over time, as indicated, e.g., bychange in the weight of the user.

The display in the fitness arc 34, by moving in the left or rightportions, can be seen to denote how far the user can be from goodfitness behavior, e.g., as indicated by weight neutral behavior. Thefitness arc 34 scale can be set so that if the combination of indicatedfood consumption and indicated activity performed produces a full energyexcess red arc portion 34 b for a given period of time, e.g., for sevendays, then the user can have gained a predictable amount of weight,e.g., at least one pound, in that given period of time, e.g., one week.If the combination of indicated food consumed and indicated activityperformed produces a full energy deficit green arc portion 34 a, againfor a given period of time, e.g., for one week, then the user can havelost the predicted at least one pound in that week. In this way fashion,an accurate prediction of weight change can be maintained, e.g., as longas the intrinsic metabolism of the user and the user's pattern ofidentifying indicated food intake and/or indicated activity type andamount also remain the same or essentially so.

Variations in indicated food intake versus indicated activity,therefore, can then be used to inform the user as to the expected affecton weight as well as on an overall health quotient 42, as discussed inmore detail below. With variation in indicated food intake and/orindicated activity, either due to change in behavior by the user orchange in the way of inputting the indicated behavior of the user, e.g.,vis a vis food intake and/or activity, on a more or less real timebasis, the system 10 can advise the user as to how much variation in theone or the other can be needed to achieve a certain weight.

Should the application 12 then show an indication(s) that it cannot makesuch predictions accurately, e.g., the constant (i.e., intrinsicmetabolism) can be recalculated and/or new values can be assigned to anindicated parameter(s) so that they can be weighted in a way thataccounts for the observed variability, leading from, e.g., a user's overor under indication of real food intake and/or real activity. By way ofexample, the greater the variability of the user inputs from the realityof the food intake and/or activity, the greater can be the value for thederived increase or reduction in the weightings assigned to that valuein the calculations by the algorithm. In other words, the intrinsicmetabolism can be a constant derived from measured values (as a functionof user input, e.g., for food intake and activity) which themselves canbe defined by tolerance parameters assigned by the application 12itself, e.g., referenced against actual indicated weight change, and thecurrently determined constant for the intrinsic metabolic rate of theuser.

In an embodiment, the fitness arc 34 can be used to depict therelationship between two power equations. The first power equation,e.g., can measure the rate of energy transfer, and the second powerequation, e.g., can measure the movement of a fixed mass over aspecified distance per unit time. The relationship expressed in thefitness arc 34 can be, e.g., a percentage change between the expectedand observed value of each power equation. The percentage change of eachequation can be given a weighted value and then the two can be summatedto produce a graphic representation, e.g., of relative change against anabsolute weight unit. The first and second power equations are discussedin more detail below.

Power Equation 1

In power equation 1, power P can be defined as the rate at which energycan be transferred or consumed, and food units can be calculated, e.g.,to be user specific, as units of energy taken in by the user. Anotherway to express this can be the familiar “calories in vs. calories out.”Once calculated, food units and energy used units can form the basisupon which a metabolism for the user for a given level of indicatedactivity undergoes an update as to the rate at which the user actuallyconsumes the indicated amount of intake of food units. The food unitscan be seen as energy equivalents which can have different values fordifferent foods, types of food and even different users. Food unitvalues can then be assigned, e.g., by the ability of a given indicatedvalue for the food unit(s) to effect weight, and not by an absolutecaloric amount. These food units may be, by way of example, assigned aninitial value based upon a published caloric content. The algorithm ofthe application 12, can then reassign a value(s) to some or allindicated food(s) intake(s) periodically, e.g., on a weekly basis, e.g.,based on how the food(s) affects the weight of the user.

The application 12 may do this, e.g., by maintaining ratios of initialassigned food values versus learned/established value(s) such that theability to affect the weight of the user as determined from the currentvalue for the intrinsic metabolism for the user and the indication(s) offood intake by the user can be used to determine a value for a foodunit. Thus an extra 3500 calories (i.e., the number of calories requiredto gain one pound) may be more or less than the food units as used bythe application 12 to change and/or predict a change in the weight ofthe user by a given amount, e.g., by one pound. Once the value of energycan be assigned to a food unit, as an example, a weekly allotment offood(s) can then be used to determine the ratio of the food units (e.g.,calories) of the food(s) to the food units used by the application 12,and can be extended to all food analyzed by the application, at least asa starting value, regardless of whether or not that particular food hasbeen consumed and thus previously analyzed by the intrinsic metabolismcalculation.

Power Equation 1:

Power P=E _(t)

where E_(t) is the energy transferred to the user from that stored infood units indicated to be consumed by the user to the energy needed tobe used up (indicated to the system 10 to be used up or predicted by thesystem 10 to be used up, by the user (over some period of time) in orderto maintain the total metabolism of the user (including the currentconstant for intrinsic metabolism of the user) so that there can be nochange in weight during a given period of time, e.g., in the course ofone week. It can be understood that this may be expressed as a ratio ofenergy in to energy out (user total metabolism) or the ratio of energyin to the energy consumed by the excess activity of the user over andabove the intrinsic metabolic rate of the user.

The rate of energy transfer can be estimated from the rate at whichweight can be gained or lost. The unit of energy can be defined, e.g.,by the number of food units necessary to maintain a stable body weight,given an indicated level of energy used by the user in the course ofactivity by the used as indicated by the type and amount of activityinput by the user and the activity module, as discussed in more detailbelow. In an embodiment, the food unit energy value can be establishedby determining how many food units can be consumed over a period oftime, e.g., one or two weeks in which there can be variability inweight. The variability in weight can then be referenced against thevariability in food units taken in to determine the number of food unitswhich would result in a change of one pound in weight, also referencedto indicated activity level(s).

As an example, the number of food units minus the number of food unitsattributable to the addition of one pound can be identified by the term“expected value”. It can be understood that the same estimation can bemade for a pound of weight that can be measured to be lost. The“expected value” can be the number of food units that, for the specifiedtime of the day, and the actual/predicted activity level(s) theapplication 12 anticipates the user can consume. If the “expected value”can be consumed in each interval (and the activity units described belowcan be known/predicted, e.g., held constant), the user can maintainweight neutrality over the course of the given period of time, e.g., oneweek. The 10 minute processing of the relationship between the expectedand the observed can then be displayed in the fitness arc 34. Indifferent time periods, a different number of food units may beexpected. The “expected food units” during, e.g., a ten minute timeframe can be used as the number of units that would maintain weightneutrality and the observed variance from expected food units could beused to determine the rate at which energy can be being transferred toi) fat which can be stored energy (i.e., weight gain), or ii) removedfrom energy stores and converted to heat plus kinetic energy (i.e.,weight loss).

The food unit increase or decrease from “expected” can be expressed as a(+) or (−) percentage. This percentage can be used in the fitness arc34. More particularly, a negative percent that shifts the fitness arc 34to the left can indicate an expected weight gain, and a positivepercentage that shifts the fitness arc 34 to the right an expectedweight loss. The units in the fitness arc 34 can be based upon relativevalue units or units of percent change. The affects of the powerequation 1 on the fitness arc 34, as noted, can be modified by the powerequation 2, discussed in more detail below.

Power Equation 2

In power equation 2, power P′ can be defined as the rate at which workcan be performed. More particularly:

Power Equation 2:

Power P′=Force*Displacement/time.

Where force can be the energy needed to move a pre-specified mass apre-specified distance per unit time.

Force can thus be defined as the ability to move the weight of theindividual user (i.e., mass) a pre-specified distance in a pre-specifiedtime. The pre-specified distance can be that which the individual can beable to move in an allotted time. The allotted time, as is disclosed ingreater detail below, can be that time allowed by the programming of amotion sensor (e.g., an accelerometer) located in the activity module 14worn by the user, which can, e.g., be used to count each deflection ofthe motion sensor (e.g., accelerometer) in a specified general directionas a separate event. This time, may be, e.g., measured in fractions of asecond. The distance traveled can be seen to depend upon the ability ofthe user to move his/her weight a given distance, which can be fixed bythe individual's current unique locomotion characteristics. He/she canonly move so far in the time allotted no matter what his/her level ofeffort because after a brief first number of milliseconds ofacceleration, a terminal velocity can be reached and limit the distancetraveled. Thus the distance that the user's mass can travel during theperiod of measurement can be seen to be fixed across a wide range ofphysical activities, e.g., walking, trotting, jogging, sprinting, etc.

Human physical activity can be episodic and therefore have nonlinearacceleration. Because the time allotment between separate episodes ofacceleration can be set in fractions of a second, the activity module 14can be, e.g., capable of counting sequential and multiple events, eventhough the events may be occurring in rapid succession. This can havethe effect of allowing the activity module 14 to count activity unitsover a wide range of physical activities, as noted above, or, e.g.,swimming, jumping, weight lifting, etc. and doing so in such a way thateach count (e.g., a stride, swimming stroke, weight lifting repetition,etc., can be used to represent a user prescribed and constant activityunit, i.e., value for energy use by the user. The pre-specified timeallotment can be a specified unit of time over which the motion sensor(e.g., accelerometer) can be used to count each motion as a separateevent.

As noted above, each displacement (or each displacement in a preselectedgeneral direction, can be utilized to equal the activity count. Time canbe extended over a period of exercise or over a longer period of time,such as one week, or separately calculated and summed over the longerperiod of time. Force can be the ability to move mass (the weight of theindividual) a specified distance (measured, for example, inaccelerometer counts) in the time specified. The time betweenacceleration events of the accelerometer can be calculated by theapplication 12 as separate events. Because the application 12 can defineforce utilized by the user as a constant and displacement can bemeasured in activity units as described above, the power variance can bemeasured as a comparison of the accelerometer deflections per week.

This can be averaged over shorter periods of time, and, e.g., calculatedto an average for 10 minute intervals. However, the units ofdisplacement (activity units) of the user mass, walking or swimming, asan example and/or weight being lifted, e.g., can be expected to occur inpre-specified intervals. Therefore expected activity can also be seen asvarying according to the time of day. There can be, e.g., an expectednumber of activity units per unit time and an observed number. Thisrelationship can be represented as a percentage change whereby anincrease percentage of activity units can be utilized, e.g., to shiftthe fitness arc 34 to the left in region 34 a, and a deficiency can beseen to shift the fitness arc 34 to the right to the region 34 b. Inaddition, the entry of the activity unit percentage can also have atimed entry into the fitness arc 34 calculation regardless of whatsegment of the day in which they can be actually performed. This timingreflects the manner in which the total expenditure of energy to performwork W (wherein W=power×time) can be projected, e.g. in a physiologicmodel, rather than instantaneous in the physiologic model.

Overall, power equations 1 and 2 can each be given a relative weight andthen summed to produce a percentage change in observed versus predictedfood energy units consumed and activity unit energy expended. Thedepiction of this percentage change, taken together with the effectsnoted above as to indicated/predicted food intake, can result in thevalue shown on the fitness arc 34. The fitness arc 34 can thus representabsolute energy excess versus energy deficit or energy excess versusenergy per unit time in specified units. The units can be defined in thepower equation calculations, but where the fitness arc 34 can beexpressed as a percentage change, the units need not be indicated to theuser. Any units for the value shown on the fitness arc also would notprovide any additional meaning because the fitness arc can be seen to bedefined for each user and have value only in that the fitness arcrepresents a unit of comparison of energy balance for the particularuser.

The application 12 can reference published calorie value(s) of aparticular food being consumed by the user, but does not necessarilydefine the value inside the algorithm, particularly considering that thecalculations within the algorithm can be based upon how the userrepresents the food intake and the impact of the represented food intakealong with the represented activity level(s) impacts weight variance forthe indicated food intake, when weighted against indicated physicalactivity, and considering the current value for intrinsic metabolism ofthe user. The published calorie content of food may be completelycoincident with a food unit value, but the calculations of the algorithmused in the application 12 do not require any such equivalence foraccuracy of its intended functions.

Calculated food units values can be independent of actual caloric intakeused in the application 12 to describe the user's metabolism. The usercan be enabled to know his or her metabolism's energy balance expressedas change in a fitness measure, e.g., an absolute and/or percentagechange in weight over a given period of time, e.g., the loss or gain ofone pound in one week. The display of this relationship on the fitnessarc 34, on which, as noted, there can be no units, can be viewed as adegree of colored filling of one or the other of the two portions of thearc of the graph, i.e., 34 a, 34 b. The energy units can be derived fromthe power equation 1 which quantifies the rate of energy intake, which,to the extend such exceeds the intrinsic metabolism for the given user,and if not expended, can be transferred into stored energy (fat), whichcan be expended in the form of energy used in activity by the user,i.e., energy units taken in modified by the power equation 2, (i.e., themovement of the individuals mass over a specified distance per unittime).

Since movement requires that force be delivered over a specifieddistance in a specified time on a specified mass, an energy unit can bederived which can predictably modify the fitness arc 34 energy transferrepresentation in a manner which reflects an energy balance (at least apredicted energy balance) for the user, e.g., at 10 minute intervals.Therefore, the fitness arc 34 can be used as a representation of energybalance as quantified by the energy transformation of food into fat orfood into physical activity per unit time, such as, the relativemovement of the mass of the individual user over distance per unit time.

It should be understood that the calculation for weight gain can bemathematically the same as the weight loss calculation. The calculationscan be weight neutral algorithms. For instance, in the weight gainalgorithm, one pound can be added to the neutral or per unit time, e.g.,weekly, base weight. In this way the application 12 can allow the userto gain one pound each week by eating calories in excess of the numberneeded for weight neutrality. The intra-week calculations can beutilized, e.g., to allow for appropriate calorie (food unit) intake tolimit weight gain to the desired one pound per week, taking intoaccount, as noted above, the energy expended or to be expended by theuser in the week. More specifically, in the weight gain algorithm theuser can be instructed to push the fitness arc 34 into the red or energyexcess portion 34 b of the fitness arc 34. If at the end of the givenweek, the user weight of the user can be more than the desired weightgain, the food unit allowance can then be readjusted downward, toprovide less extra calories for achieving the desired weight gain of onepound in the next week.

Continuing to refer to FIG. 6, in an embodiment, located above thefitness arc 34 can be a series seven color coded dots 36. At the end ofeach day the fitness arc 34 can be used by the application 12 to assigna color to one or more (?) dots 36 representative of a given day of theweek. The current date can be located in the bar above the dots 36, andthe dot 36 corresponding to the current date can be indicated, e.g., bybeing underlined (not shown in FIG. 6). There can be one dot 36 for eachday of the week. The series of seven color coded dots 36 can beutilized, e.g., to summarize the fitness arc 32 results for each of theseven days. The dots 36 may be green to indicate positive fitness gainfor a given day, black for neutral, or red for weight gain. For a givenday, the dot 36 can be green if the fitness arc 34 can be fully green,red if fitness arc 34 can be fully red, and black if the fitness arc 34is not a full color. The accumulation of 7 green dots 36 can indicatethat the expected one pound of weight loss should have occurred, and amixture of color dots 36 can be seen to indicate a variable effect onweight and fitness. The occurrence of a red dot 36 can be seen toindicate a slower progress with the weight loss process. The energyintake excess, e.g., as indicated by the red dot 36 can indicate theundesirable effect of resetting the body of the user to a natural statewhich can be to store fat rather than break it down. Day to dayvariations, particularly of more than ½ of a pound, can be most likelyfluid gain or loss. These variations can be difficult to interpret inisolation. The system 10 over time can calculate actual changes in bodymass that, e.g., are not the result of water weight fluctuations.

Continuing to refer to FIG. 6, in an embodiment, a circular shapedactivity circle 38 can be utilized to indicate the amount of physicalactivity (e.g., exercise or motion) achieved for a given day, or,alternatively, cumulatively over the given longer time period. Theactivity circle 38 can be filled using data provided from the activitymodule 14, e.g., wirelessly. The activity module 14, as noted above, canrecognize different types of activity, such as aerobic, intense aerobic,weight training and intense weight training, as disclosed above and infurther detail herein below.

The activity circle 38 can represent the expected activity of a user,e.g., based upon the history of the amount and type of activityperformed by the user. If the behavior of the user changes, the amountof activity needed to fill the activity circle 38 can be changed. Noindividual has the same level of activity from day to day. Theapplication 12 can adjust the user's food allowance throughout the daybased upon what activity can be expected and what has actually occurred.The activity circle 38 can fill up at different rates, for the samenumber of activity units, for different users. In other words, the ratefor filling the activity circle 38 for any given exercise can bevariable for each user and also can be partly or fully based on alearned activity pattern learned by the application 12, based upon theprior behavior of the user. In an embodiment, should the user conductmore activity than the application 12 historically expects, the activitycircle 38 can display progressive series of colors indicating the amountof activity increase. Changes in the activity circle 38 can have animmediate impact on the fitness arc 34.

Any prediction made in determining the fitness arc 34 (i.e., thecalculation of an energy deficit/energy excess) may be confirmed throughthe input of the user's daily (or other periodic entry) actual weight.If the prediction by the system 10 is incorrect, the system 10 can adaptto the user's circumstances. For example, if the user underestimates theindicated food intake portions, the user may gain weight, even thoughthe fitness arc 34 indicates an amount on the energy deficit side 34 aof the fitness arc 34. As disclosed above, the application 12 canrecognize this and make adjustments that enhance the accuracy of thefitness arc 34 accordingly. Similarly, if the user does not burncalories as rapidly as initially predicted (and therefore an initialprediction by in the energy deficit portion 34 a may result in an actualenergy excess), the application 12 can recognize this and adjust thefitness arc 32 accordingly.

The units which describe activity and food choice can be specific toeach user, and can be learned for each individual and adjusted daily.For example, they can be different from the conventional food caloricunits, which can be used as measurement of physical activity, or theunit of energy liberated in heat generation from a specific food. Thefood calorie units can be entered into the application 12 initially, butthe units change as they can be measured against other variables, andthey can be assigned a unique user specific number within the algorithm.There can be constants assigned to the user, e.g., which representintrinsic metabolism, but this number can be recalculated as food iconselections, activity and fitness affect the user's actual and changinglevel of intrinsic metabolism.

The application 12 can consider metabolism as the efficiency with whichthe user utilizes stored and consumed calories and therefore representsan element of the energy balance. Thus calories assigned to food oractivity for example, can be different from those assigned from existingdata bases, but instead can be defined by the way in which the userinputs data and the way the data as input interacts to establish themetabolic constant calculated by the application 12. The values assignedcan be recalculated based upon their ability to accurately predictweight gain or loss. The fitness arc 34 can represent a real timepresentation of the system 10 assessment of the energy balance. In anembodiment, the fitness arc 34 periodically updates (e.g., every 10minutes) and displays the energy balance relationship between food,activity and metabolism. As described hereinabove, at the end of eachday, the fitness arc 34 data can be assigned a final value which thencan be represented by the green, red, or black dot 36. The ratio orproportion of the color coded dots 36 over, for example 7 days, canvisually inform the user as to whether there can be an expected weightloss or gain during a particular week. The algorithm thus creates anongoing user profile of intrinsic metabolism, activity, food choice andfood amount that can be unique to each user.

Continuing to refer to FIG. 6, a colored diamond-shaped pointer 40 canbe movable along a line that represents a range of a health quotient 42.The health quotient 42 can be derived from the running average of thefitness arc value 34 c for each day of a month modified by the food typeconsumed and the user's weight. The health quotient 42 can include theuser's present weight and desired or targeted weight (i.e., via directinput), the quantity and type of food consumed (i.e., based on theuser's selection of food types and quantities). The health quotient 42also can include the aerobic activity of the user (such as running) andanaerobic activity (such as resistance training for muscle enhancement)which can be automatically input into the application 12 by the activitymodule 14 as disclosed in more detail below.

In an embodiment, the health quotient 42 can be a graphic representationof a single point on a horizontal scale of the health and fitness of theuser as referenced against his/her goals and profile. The healthquotient 42 can be contrasted to the fitness arc 34, which can be ameasure of daily energy balance, because it places the user on a scaleof fitness and health based on data accumulated over longer periods,e.g., one month. The determination of health can be not culled ordetermined from a demographic reference point, but instead determinedfor each user based upon parameters defined in the application 12 (i.e.,target weight, calculated intrinsic metabolism, food type and quantityconsumed, the rate of change in weight gain or loss of the user,exercise and activity units level, etc.). The health quotient 42calculation can incorporate the directionality of measured values andinputs for the user to establish health status. The health quotient 42also can be given limitations as to its positioning on the scale basedupon indicated weight goals. Specifically, the overweight individual(defined in the user profile input screen 24 by a targeted weight goalless than actual weight) could be restricted from a pointer 40 positionon the fit zone of the health quotient 42 horizontal scale. The locationof the pointer 40 on the horizontal scale can also be determined byhistoric data from the user as well as daily updates which, whenformatted by application 12, define the health quotient 42. Thehorizontal scale can be a range of units for all users allowing forstandardization and comparison among individuals and groups, but thedata and profile for each user defines the degree of movement on thescale conferred by the various parameters of the algorithm(s) used inthe application 12. In other words, the scale can be constant across allusers, but the amount of change or movement on the scale per calculatedvalue(s) of the application 12 parameters can be different for eachuser. Thus the user can set individual goals, but where the pointer 40can be positioned on the health quotient 42 scale can be based upon theapplication 12 algorithms' calculation of the user's specific metabolicprofile.

As disclosed above, the starting weight 24 b and target weight 24 d canbe input on the user profile input screen 24 (see FIG. 3). Based onthese inputs, one of two conditions can be possible: i) the user can beover weight (i.e., the starting weight can be greater than the targetweight), or ii) the user can be at or under the target weight. These twopossibilities can be used to govern the health quotient 42. Moreparticularly, in an embodiment, when the health quotient 42 iscalculated at the end of each day, the pointer 40 can be positioned in amanner described below.

The health quotient 42 horizontal scale can range, e.g., from −50 unitsat the left end to +50 units at the right end, although the numericalvalues for the units are not shown on the scale on FIG. 6. Each month, arunning average of available health quotient 42 daily results can becompiled and displayed. When moving from one month to the next, thefirst day of each month can be equivalent to the final figure from theprevious month, and it can be weighted as only one day of that month. Asshown in FIG. 6, the horizontal scale can be divided into four portionsmoving left to right. The first portion extends from −50 to −25 and canbe labeled “fit”, the second portion extends from −25 to 0 and can belabeled “healthy”, the third portion extends from 0 to +25 and can belabeled “unhealthy”; and the forth portion extends from +25 to +50 andcan be labeled “health risk”. In an embodiment, each portion may havecolor coding varying from “fit” to “health risk” such as dark green,green, yellow, and red, respectively. The position of the pointer 40 onthe horizontal scale can be used to represent, at the end of each day,that month's average of health quotient 42 values over the availabledays in the month. Furthermore, the health quotient 42 units can be thefitness arc values 34 c of the fitness arc 34 at the end of each day,e.g., as modified in a manner described below.

In an embodiment, the health quotient 42 may also account of thedistribution of the calories consumed thought the day. Moreparticularly, the waking hours are divided into four quadrants. If 20percent of the total food consumption is consumed in each of the fourquadrants, then the pointer 40 will shift to the left by three units,and if not, it will shift to the right by three units. The remaining 20percent can be consumed in any of the four quadrants without effectingthe health quotient 42.

In the circumstance where the user is over weight (i.e., the startingweight can be greater than the target weight), the pointer 40 can pointto a point to the left of −24. The user could thus be in the “healthy”range but not in the “fit” range. Food selection can also modify thefinal number. Each food item can be assigned a color: for example redfor poor quality, yellow for neutral quality, and green for high qualityfood. Further, when consumption of 51% of food is good quality or poorquality then the following modifiers can be activated, and ifconsumption of either the good or poor quality food does not reach 51%,then these modifiers may not be activated. The modifiers and theirtriggers can be:

If 51 percent of food consumption is “good quality” and the user isoverweight then the final fitness arc 34 can have negative, e.g., 12units added to fitness arc value 34 c and the pointer 40 can be shiftedto the left. If 51% of food consumption is poor quality, then thepointer 40 can be shifted to the right, e.g., by 12 units.

If the user is at or under target weight and 51% percent of foodconsumption is “good quality” then the pointer 40 can be shift, e.g.,(50+12) or 62 points to the left. If 51% of food consumption is “poorquality”, then, as described above, the pointer 40 can be shifted, e.g.,to the right by 12 units.

The system 10 can also reference food intake with change in the user'sweight and fitness activity to develop the user's intrinsic metabolism.As described above, the system 10 may adjust the prediction of changesin the health of the user on a daily basis based on input values fromthe user regarding weight, food intake and fitness activity.

In an embodiment, a summary of each month's health quotient 42 may bedisplayed (not shown). For example, the display may provide a listingsuch as: i) January—fit, ii) February—unhealthy, etc.

Referring now to FIGS. 7A-7C, as described above, when a user consumesfoods, it may not be necessary for the user to directly input the numberof calories. Instead, the user may select the type of food consumed froma listing 44 as shown in FIG. 7A and further defined in the listingshown on the screen as indicated by way of example in FIG. 7B. In anembodiment, the application 12 may learn the user's most frequentlychosen or consumed food choices, and compile the same under a tab on thelisting 44 (see FIG. 7A “favorite foods” tab 56). A dietician can reviewthe listing 44 and repopulate it. When the user can read calories off afood package, the item may be entered directly on the screen depicted inFIG. 7C. In such instances, the food percentage of protein, fat, etc.components may be provided by the application 12 for such items, basedon the normal distribution of these components for such items. In anembodiment, the listing 44 may include items such as deserts and junkfood (not shown).

Referring to FIG. 8, in an embodiment, once a type of food is selected,a portion screen 46, including a plate 48, can be displayed. FIG. 8 alsodepicts a knife 50, or some other utensil for a size reference. The usermay place more or less food 52 on the plate 48, e.g., with portioncontrol buttons 54 a, 54 b. In an embodiment, the knife 50 can fill witha color scheme which depends on the portion size of the food 52, wherethe degree of coloring of the knife 50 equates with the degree offilling of the food circle 20 (FIG. 2) allowance. This can allow theuser to visually input the type and portion of food, without the need ofmeasuring, weighing or knowing the caloric content of the food. In anembodiment, the listing 44 may include an option for the user to input(e.g., download) a new food item(s) on the listing 44. The user may alsomanually directly input a caloric intake item.

In an embodiment, the user may enter a “proposed” meal to determine themeal's effect on the user's fitness goals. The user may then edit theproposed meal or change the proposed meal into an actual meal, e.g.,after the meal is consumed. In an embodiment, the impact of the proposedmeal on the user's food and caloric balance can be demonstrated by theknife 50 progressively filling with a color scheme which matches thecolor scheme and the degree of filling of the plate 48. Thus before theuser enters the content of the meal into the application 12, the effectof the proposed meal can be seen by reviewing how much color the knife50 has filed in. Reducing a food portion size can decrease thepercentage of the knife 50 coloring. A fully colored knife 50 can beused to correspond to a fully colored food circle 20.

In an embodiment, in addition to accumulating and displaying fitness andhealth related data generated by the application 12, the system 10 canfacilitate accumulating and displaying externally generated fitness andhealth related test results, thereby serving as a focal point foraccumulating, storing and displaying all fitness and health data relatedto the user, not just the data provided by system 10. For example, testresults may be periodically input in the application 12 by the user on atest results record screen 58 shown in FIG. 9. In an embodiment, FIG. 9includes data on total cholesterol 60, LDL cholesterol 62, HDLcholesterol 64, triglycerides 66, fasting glucose, 68, hemoglobin A1C70, blood pressure 72, and percentage body fat 74. It can be understoodthat other test results data may also be included in the test resultsrecords 58. The application 12 can then utilize the test results recordscreen 58 data to form historical graphs or histograms. For example,FIG. 10 depicts a graph or histogram 76, which shows total cholesterol60, LDL cholesterol 62, HDL cholesterol 64, and triglycerides 66 bloodtest results for the user taken at various dates. Further, since energyexcesses 34 b may raise cholesterol levels, energy excesses 34 b may becalculated and displayed (not shown) on the histogram page 76.

Referring to FIG. 10, in an embodiment, the system 10 can generateparameters such as the fitness arc value 34 c, the health quotient 42,and the breakdown of food percentage 43 a, 43 b, 43 c, etc., which mayalso be displayed in the histogram 76, to show correlations between thesystem 10 derived parameters and the externally derived test results(e.g., total cholesterol 60, LDL cholesterol 62, HDL cholesterol 64, andtriglycerides 66). In an embodiment, FIG. 11 there is illustrated, byway of example, a histogram 78 for displaying test result measurementssuch as fasting glucose 68, hemoglobin A1C 70, and percentage body fat74 over time. The system 10 may also generate other histograms (notshown) for displaying, e.g., the percentages of protein, fat, andcarbohydrates, so that the food choice percentages utilized by the userand their trends over time can be also readily apparent to the user.

In an embodiment, the system 10 can facilitate accumulating anddisplaying data that can be related to health conditions that are beingmedically treated by the user. For example, Coumadin is a blood thinnerprescribed to patients with a propensity to form blood clots in thevascular space. Such patients must monitor their intake of vitamin K(Vit K), which diminishes the effectiveness of the blood thinner. Vit Kis known to occur in certain foods such as vegetables. The diet forpatients on Coumadin therapy may be not focused on Vit K avoidance, butrather it can be based on the consumption of the same amount of Vit Keach day.

Referring to FIG. 12, Vitamin K chart 80 includes a Vit K circle 82which can provide a graphical representation of the user's dailyconsumption of Vit K. If the diet of the user fills the Vit K circle 82the same amount each day, then the effectiveness of the Coumadin therapycan be maintained. The Vit K circle 82 functions in much the same manneras the activity circle 38, and it can be learned for each user. Theapplication 12 can learn and then stores a weekly average value of Vit Kunits which serves as a record of the user's Vit K units consumptionbehavior. The Vit K circle 82 may fill with green color as the units areaccumulated toward the weekly average. More particularly, a numericalvalue of 1, 2, or 3 Vit K units can be assigned to each vegetable inorder to describe its Vitamin K level. For example, if the user ate 100calories of food assigned the numerical value of 1 Vit K unit, theapplication 12 could register 100. Vit K units on Vit K circle 82. Ifthe user consumed 100 calories of food assigned the numerical value of 2Vit K units, then 200 Vit K units could be registered on the Vit Kcircle 82.

The user can choose, on the profile input screen 24, whether to displaya circle depicting whether the food consumed includes the total dailyvitamin requirement or Vit K alone. The Vit K circle 82 may also fillwith a green color (denoting a full daily allotment of Vit K has beenreached), a yellow color (denoting a full daily allotment of Vit K 1 isbeing approached), or a red color (denoting a full daily allotment ofVit K 1 has been exceeded). In an embodiment, the Vit K circle 82 mayalternately be displayed adjacent to the fluid and salt circles 26, 28on FIG. 4 (not shown in FIG. 4).

Referring now to FIG. 13, as described above, the application 12 caninclude software algorithm codes for displaying data, calculating data,receiving data etc. In an embodiment, the application 12 can include anapplication algorithm interface 84 which can facilitate the interactionsbetween the digital device D and the application 12 in a predetermined(e.g., standardized) manner. For example, the application algorithminterface 84 can enable the application 12 to utilize the conventionalservices and functions of the digital device D, such as i) the centralprocessing unit, ii) the input/output interfaces (e.g., touch screen,keyboard, mouse, etc.), and iii) the Bluetooth™ transceiver. In thisway, the software algorithm codes of the application 12 may employ theseservices to receive data, display data, and calculate using the data,etc. In an embodiment, the application 12 can be functionally organizedaround a processor/logic unit (computing device) 86 that can beconnected to a food units manager 88, an activity units manager 90, aweight units manager 92, an intrinsic metabolism manager 94, and theapplication algorithm interface 84.

In an embodiment, the food units manager 88 and the weight units manager92 can be interacted with the user via the user interface of the digitaldevice D, and the activity units manager 90 can interact, e.g.,wirelessly, with the activity module 14, e.g., via the Bluetooth™channels BT1 and BT2. The results of the food units manager 88, theactivity units manager 90, and the weight units manager 92 interactionscan be input to the processor/logic unit 86 wherein the application 12can periodically run the energy balance calculation and formulate theintrinsic metabolism and provides the same to the intrinsic metabolismmanager 94. In the manner described above, the intrinsic metabolismmanager 94 can assess the accuracy of the processor/logic unit 86formulated predicted weight to that of the inputted actual weight of theuser. Should the formulated/predicted weight be significantly differentthan the actual weight of the user, the intrinsic metabolism manager 94can, e.g., direct the processor/logic unit 86 to formulate anadjustment, e.g., to coefficients provided to the food units manager 90for adjusting the food unit values or to the activity units manager 90for adjusting activity units as is further discussed below.

FIGS. 14A and 14B depict the activity module 14 which, when it can beworn by the user, can produce and stores activity units that can beconveyed, e.g., wirelessly, to the application 12. More particularly,the activity module 14 can be contained in a disc-shape housing 96 whichcan have a face 98, a bottom 100 which can be positioned opposite theface 98, and a cylindrical-shaped side 102 which extends between theface 98 and the bottom 100. In an embodiment, the bottom 100 may bereleasably attached to the side 102 (e.g., threaded or clipped thereto)to facilitate the fabrication of the module 14 as well as, e.g., thereplacement or recharging of batteries. The housing 96 may be made ofplastic or other suitable material such as stainless steel. The activitymodule 14 may have a Bluetooth™ connection to application 12 of thesystem 10.

In an embodiment, the housing 96 can a plurality of indicators andbuttons. More particularly, two buttons 104 can be positioned oppositeeach other on the side 102 of the housing 96. The user may turn theactivity module on and off, e.g., by simultaneously pressing the buttons104 with the thumb and forefinger and briefly shaking the activitymodule 14. The activity module 14 can shut down when it comes to restfor a selected period of time and can turn on when it senses motion. Inan embodiment, both buttons 104 must be pressed simultaneously for alloperations that require input from the buttons 104. An arrow-shapedpointer 106 can be located on the face 98 of the housing 96, forpurposes disclosed below.

In an embodiment, the activity module 14 has magnets 108, 112 and anindicator light 110 that can be illuminated to indicate a low batterycharge. The arrow shaped pointer 106 may also signal that the activitymodule 14 has the proper orientation in an exercise band 118 (FIGS. 15A,15B), e.g., to record an aerobic exercise monitoring mode or a weighttraining exercise monitoring mode, which can be disclosed below.

In an embodiment, the activity module 14 can have a plurality ofactivity lights 114 which can be positioned on the face 98 of thehousing 96, e.g., in a circular pattern to form an activity circle 116.The activity lights 114 e.g., can be progressively lit up during the dayto indicate the user's progress in achieving his/her daily goal foractivity units. A blinking activity light 114 can indicate that theactivity units goal attributed to that particular activity light 114 hasnot yet been achieved, and a steadily illuminated activity light 114 canindicate that the activity units goal associated with the activity light114 has been achieved. The activity circle 116 goal can be the number ofactivity units that can be required to be achieved by the user in theday to maintain his/her weight, or to be exceeded to lose weight, or tobe under-achieved to gain weight and each of the activity unlit lights114 in the activity circle can represent a percentage, e.g., 25% of thisamount. In other words, the activity circle 116 activity units' goal canbe also equal to the sum of each of the activity light's 114 activityunits goal.

Assuming that the food intake is in a specified range, should theactivity unit exceed expected levels, the daily food allowance can beincreased as represented in the food circle 20 (FIG. 2). The object forthe user can be to light up all the activity lights 114 during the day.The activity units circle 116 goal can be the same as that which can beapplied to the activity circle 38 depicted in FIG. 6. The activitycircle 116 goal, which can be calculated by the application 12, can betransmitted to the activity module 14 from the digital device D via thechannel BT2. The number of activity units accomplished by the user atany given time in the day may be transmitted from the activity module 14to the digital device D via the channel BT1. The activity module 14 canupdate its activity circle 116 independently from the application 12,once the activity module 14 has been informed by the digital device Dhow many units are required to illuminate all of the activity lights 114of the activity circle 116. The transfer of activity units' data can beaccomplished during a synchronization process which is discussed below.

In an embodiment, the user can synchronize the activity module 14 withthe application 12, e.g., by pressing and holding the buttons 104 anddouble shaking the activity module 14. The activity module 14 can bethen positioned within five feet of the digital device D, and the Synctab located below the fitness arc 34 (see FIG. 6) can be then pressed.During the synchronization process, i) the activity units goal that hasbeen calculated by the application 12 can be transmitted to the activitymodule 14 from the digital device D via channel BT2, and ii) theactivity circle 38 of the application 12 can fill with accumulatedactivity units that can be transmitted to the digital device D by theactivity module 14 via channel BT1. The user may synchronize theactivity module 14 with the application 12 as many times as desiredthroughout the day, but preferably at least once a day.

In an embodiment, the activity module of the described invention caninclude a processor, a motion sensor, a timer and a rechargeablebattery. In another embodiment, the motion sensor is an accelerometer.In another embodiment, the accelerometer is a triaxial accelerometer.

In an embodiment, the activity module can be programmed to alter theperformance of the processor and the accelerometer to track differentexamples of motion. Such examples of motion include, but are not limitedto, movements associated with sleep, walking, jogging, running, weightlifting, biking, yoga, Pilates, circuit training, resistance training,elliptical training, tennis, basketball, soccer and the like.

In an embodiment, the environment of the motion sensor, e.g.,accelerometer, can be engineered (i.e., placed) in differentorientations within a magnetic field to change the performance of themotion sensor, e.g., accelerometer, for the specific category of motionbeing performed. This engineered magnetic environment can excludecertain movements of the motion sensor, e.g., accelerometer, notassociated with a particular activity. Activities include, but are notlimited to, sleep, walking, jogging, running, weight lifting, biking,yoga, Pilates, circuit training, resistance training, ellipticaltraining, tennis, basketball, soccer and the like. The engineeredmagnetic environment can allow for the segregation of various types ofactivity into analyzable units.

In an embodiment, the described invention provides a system in which auser can place the activity module into pre-specified positions inside amagnetic field. The magnetic field is created, for example, by magnetscontained within a receptacle (e.g., a pouch, a pocket, etc.) connectedto a means for attaching the activity module to the user (e.g., a band,a strap, etc.). The performance characteristics of the activity modulecan be programmed to detect a specific type of motion while excludingmovement which characterizes other forms of activity. The activitymodule can be programmed, for example, by operating buttons located onthe activity module, by a command transmitted via Bluetooth™ from adevice, which includes but is not limited to, a communication device, anetwork device, a personal digital assistant, a mobile communicationdevice, whether or not able to download and run applications from thecommunication network, such as the Internet, e.g., an I-Phone®,Blackberry®, Droid™ or the like, a manufacturing tool, or any otherdevice including a computing device, comprising one or more dataprocessors, etc., or by orienting the activity module in variouspositions inside the magnetic field.

In an embodiment, the described invention provides a magnet or a seriesof magnets located in a tube or series of tubes encircling the activitymodule (e.g., accelerometer). The location of the tube or series oftubes includes, but is not limited to, within the means for attachingthe activity module to the user (e.g., a band, a strap, etc.), withinthe casing of the activity module, and the like. The motion of theactivity module (e.g., accelerometer) when performing various activitiescan produce different speeds and patterns of movement of the magnet orseries of magnets within these tubes. This pattern of movement can beused to further characterize the user's activity and increase theaccuracy of the activity module's characterization of the user'smovements. A non-limiting example of the magnet or series of magnetsincludes a sphere. The location of the magnet or series of magnetswithin the tubes includes, but is not limited to, a dynamic (meaning notfixed or static) position. By way of example, dynamic movement ofmagnets shaped as spheres inside one or multiple tubes encircling theactivity module (e.g., accelerometer) activates the electronics indistinctive patterns which the processor recognizes as beingrepresentative of different activities. For example, movement of one'sarm during swimming creates a pattern of movement of the magneticspheres inside the tube or tubes that is distinguishable from thepattern observed when the user is running.

In an embodiment, the described invention provides a combination of auser activated switch and magnetic field to institute programmingchanges to alter the functional status of a motion sensor, e.g., anaccelerometer, into different activity monitoring modes. Activitymonitoring modes include, but are not limited to, a standard mode (“S”)selected for routine daily activity, a running/jogging mode (“A+”), abicycle riding mode (“A”), a weight lifting/resistance training/yogamode (“W+”), an aerobic-based gym equipment (e.g., elliptical) mode(“W”) and a sleep activity mode. By programming the motion sensor, e.g.,accelerometer, into an activity monitoring mode, the motion sensor,e.g., accelerometer, can distinguish and record the types of movementassociated with a particular activity and exclude the types of movementnot associate with a particular activity.

In an embodiment, the deflections recorded by the motion sensor, e.g.,accelerometer, do not need to be interpreted at an application interfaceto determine what type of activity or what type of motion produced aspecific deflection. In another embodiment, motion algorithms are notneeded to determine what type of activity or what type of motionproduced a specific deflection. Instead, the movement that characterizesthe activity is itself characterized in terms of, for example, timing,direction, acceleration and a multiplier.

Positioning the activity module inside the magnetic field can enable theactivity module to distinguish activities (e.g., walking, weightlifting, jogging, running, yoga, and bicycle riding) from one another.By way of example, movement which characterizes weight lifting isdifferent in timing, direction and acceleration from walking or bicycleriding. Orienting the activity module in various positions inside themagnetic field can allow for the recordation of motion associated withone type of activity, while excluding movement which characterizes otherforms of activity.

In an embodiment, movement in a particular magnetic field that isrecognized by the activity module is assigned a multiplier. Themultiplier can allow for the movements associated with one activity tobe assigned a weighted value that is different in magnitude from othertypes of activity. By way of example, the multiplier assigned tomovements associated with bicycle riding is different than themultiplier assigned to movements associated with walking, which isdifferent than the multiplier assigned to movements associated weightlifting, which is different than the multiplier assigned to movementsassociated with sleep.

Deflections (also known as counts or clicks) recorded by the motionsensor, e.g., accelerometer, for each type of movement are saved andsegregated by activity type in the activity module processor. Theinformation saved and segregated by the processor is used by theactivity module software to determine, for example, the amount ofrelative energy expended by the user during a given time period in eachof the modes of activity. For example, the activity module can determinehow much relative energy was expended weight lifting versus walkingversus running, etc. This information can be transferred, for example,via Bluetooth™ to a device such as a smart phone that contains softwarefor further processing. After such processing is complete, the activitymodule can receive further programming instructions which in turn canfurther update the activity module's displays.

In an embodiment, the activity module can be sent commands viaBluetooth™ or by operating buttons located on the activity module inorder to change performance of the activity module independent of themagnetic field. Commands include, but are limited to, turning theactivity module on/off, changing the sensitivity of the activity module,changing the type of activity, changing the activity monitoring modesand the like. Activity monitoring modes include, but are not limited to,travel mode and sleep mode.

In an embodiment, the activity module can be programmed independent ofthe magnetic field in order to count routine daily activity with numericconsistency when worn or carried in different positions on the body.Such positions include, but are not limited to, a belt clip position, agarment clip position, a lanyard position, a pocket position and thelike.

In an embodiment, data collected from the activity module usedindependent of the magnetic field can be entered into a general activitycategory or general activity ledger.

In an embodiment, the activity module includes at least one magneticfield detector component. In another embodiment, the magnetic fielddetector component is a Hall effect sensor. In another embodiment, theHall effect sensor can be connected to a processor. In anotherembodiment, the Hall effect sensor transmits a signal to the processorwhen a magnetic field is detected. The signal transmitted by the Halleffect sensor to the processor, for example, can cause the processor tochange the way it interprets signals transmitted from a motion sensor,e.g., an accelerometer, and can cause the processor to adjust the waythe motion sensor, e.g., accelerometer, captures movement.

In an embodiment, magnetic field orientation is recognized by aprocessor which transmits a signal to a motion sensor, e.g., anaccelerometer, via firmware (also known as software). The signal changesthe parameters under which the motion sensor, e.g., accelerometer,reads, collects and reports data. A combination of orientation of theactivity module within a magnetic field and the presence or absence ofswitch activation on the activity module results in the reprogramming ofthe activity module by the processor to a set of pre-specified valuesstored in the processor. These pre-specified values aid in defining theintensity of work associated with each motion sensor, e.g.,accelerometer, deflection for any given activity.

In an embodiment, the activity module includes a processor. Theprocessor of the described invention can separately store deflectionsrecorded during each of the programmed modes of activity. The activitymodule can communicate these stored deflections via Bluetooth™, forexample, to an application residing on a device (e.g., mobile phone) fordisplay either individually or in groups selected by the application torepresent various forms of activity. The display can include, but is notlimited to, what percentage of activity results from weight resistancetraining (i.e., to aid in muscle growth), what percentage of activityresults from aerobic training (i.e., to improve athletic performance orlose weight), etc. The display can allow the user to regulate certainactivities in order to select an optimal approach to obtain his/herfitness goals.

In an embodiment, the processor includes firmware (also known assoftware). The firmware of the described invention can be used to governthe relationship between the processor and the motion sensor, e.g.,accelerometer. For example, the firmware can be used to change theparameters of function of the motion sensor, e.g., accelerometer,including, but not limited to, sensitivity, scale, detection time, countminimum and release time. The firmware also can be used to change themultiplier used by the processor.

In an embodiment, the firmware of the described invention can be used todetermine the amount of effort expended in achieving a motion sensor,e.g., an accelerometer, deflection. For example, it is known that anaccelerometer measures acceleration or the rate of change in speed overtime but cannot measure effort or the speed at which any particularmovement takes place. That is, the effort needed to change theacceleration of the activity module of the described invention cannot bemeasured by the accelerometer. It also is known that a smaller mass willaccelerate faster with lower effort than a larger mass and that anaccelerometer cannot measure this difference in effort. As such, aconstant (i.e., multiplier) cannot be applied. However, when theactivity module of the described invention is placed in an engineeredmagnetic environment in which the kind of acceleration to be recorded ispre-specified, then a value which is reflective of relative levels ofeffort can be assigned from one activity to the next. Various types ofactivity (e.g., running versus biking) generate a different pattern ofacceleration cycles as the accelerometer moves through space. Theaccelerometer records the number of acceleration vectors it isprogrammed to detect. According to the described invention, theaccelerometer data will not be rational if the user rides a bike withthe activity module in the weight lifting position because the activitymodule would not count the rotation of the pedals with any regularityand for those it did count it would assign an inappropriate multiplier.An analysis of the accelerometer vectors as the activity module movesthrough space is not possible once the accelerometer deflection or countis generated. Thus, variance in accelerometer deflections or countscannot distinguish the type of activity performed after it has occurred.In addition, the computational power needed to analyze the pattern ofvector changes as they occurred would far outstrip the capacity of adevice such as a mobile phone. Therefore, the described inventioninstead takes the approach that by pre-specifying movements, thedeflections detected by the accelerometer are indicative of a specificactivity. A multiplier can then be assigned at the level of theprocessor to indicate greater or lesser levels of effort (i.e. work);not because the accelerometer recognized the effort, but because theaccelerometer was only allowed to record certain movements that typifycertain types of activity. The movement between one activity and anothermay not be sufficiently dissimilar to allow the assignment of amultiplier reflective of the assumed effort. Activities with a similarpattern of movement are therefore grouped and the user is instructed towear the activity module in the magnetic field (e.g., a strap or bandcomprising magnets). The magnetic field is detected by a Hall effectsensor, which in turn informs the processor that the movement recordedis a low or high effort activity. High effort activities can either beassigned a multiplier and/or the accelerometer can be programmed toregister a greater number of accelerometer deflections or counts perunit time. When a triaxial accelerometer is used, data can be collectedin a three dimensional manner as the accelerometer changes its vectorangles when moving through space. For example, the accelerometerattached to the wrist when walking can have a similar pattern of motionthrough space as when jogging. Therefore, when walking, theaccelerometer can be programmed to record fewer accelerometerdeflections or counts for each stride forward than when running. Thereason for such a change in programming is that it requires more effortto jog than to walk the same distance. The accelerometer deflections orcounts without the methodology of the described invention would actuallybe less for jogging because it takes fewer strides to cover a distancetraveled jogging compared to the same distance traveled walking. Thefirmware of the described invention can be used to assign moreaccelerometer deflections or counts to certain activities. Theassignment of more accelerometer deflections or counts can be considereda proxy for effort. The activity module position in the magnetic field,or mobile phone selected activities when connected via Bluetooth™,reprograms the activity module and determines what motion is to berecorded during any particular activity. When weight lifting, forexample, it is advantageous to eliminate most of the movement of theuser's arm that might occur when walking. The activity module can beprogrammed not to detect the movement associated with walking around thegym, but to detect the movement associated with lifting weights. It isunderstood that in weight lifting, the arm motion is largely linear,whereas in walking, the vector direction of arm motion is constantlychanging through an arc. There is very little acceleration of arm motionin walking that takes place in a single vector. The firmware of thedescribed invention can be used to program the activity module torecognize these differences in arm movement.

In another embodiment, the amount of effort expended can be determinedby the use of a timer in the motion sensor, e.g., accelerometer. Thetimer can be used to record the number of deflections per unit time. Thetimer can be keyed to start and stop with the beginning and conclusionof a particular exercise. The number of deflections recorded per unittime can be translated into a refinement of the calculation of theeffort expenditure different than simply recording the total number ofdeflections performed. Without being bound by theory, it is believedthat there is a limit to the velocity with which that individual cantransport himself/herself through space with each deflection. Thedescribed invention assumes this to be a constant value when performingcalculations and thus there is no need to measure it. By way of example,if a user is running or pedaling a bike, the revolution of the pedal andthe individual stride covers roughly the same distance no matter howfast the user is traveling. The only variable is the number ofrevolutions of the pedal or the number of strides per unit time. Becausevelocity is calculated as distance/time, and because for any givenindividual a distance traveled per deflection for any given activity canbe assigned, only time is needed to calculate the velocity. A timer inthe motion sensor, e.g., accelerometer, can be activated with eachseparate sequence of movements to determine how much time passes whilethese deflections are being collected. The beginning and end of asequence of deflections can be defined which allows the describedinvention to pre-specify how much time can elapse before the sequence ofdeflections is ended and a new sequence of deflections begins. The timerinitiates with each sequence of deflections and is thus constantlycycling on and off in any given activity. As described, the engineeredenvironment interprets this data, thereby providing meaning to thevelocity calculation. Because the velocity of an object travelingthrough a distance is linearly related to energy expenditure, additionalmultipliers can be assigned to each deflection, depending upon howquickly the deflections are recorded and what type of activity is beingperformed. The basic energy calculation is that of moving a known mass(i.e., weight of the user) through a specified distance (i.e., stride ofthe user, considered a constant distance multiplied by the number ofdeflections to reflect the total distance traveled) and a calculatedvelocity (i.e., the number of deflections equating to a distancetraveled per unit time as measured by the activity module's internalclock which equals distance/time or velocity). This analysis can beperformed both for cardio activities and weight lifting, howevervelocity calculations for effort are in the opposite direction forweight lifting. For example, in weight lifting mode, the speed withwhich the weight moves is inversely proportional to the weight beinglifted. A set of heavy weights generally will have less deflections perunit time. A multiplier can be assigned to the deflections in the weightlifting mode such that the recording of fewer repetitions per unit timewill be assigned a higher multiplier per deflection.

Because the activity module of the described invention is a learningalgorithm, it only needs to study the variance within the individualuser of weight loss or gain, food consumed and activity type to begin tomake an accurate assessment of energy expenditure. The timer counts thenumber of deflections per unit of time and the release time determinesthe beginning and end of each cycle of repetitions or the initiation andtermination of a specific activity. In this way, the user's energyconsumption can be characterized from the movement performed during aspecific activity.

In an embodiment, the activity module includes an accelerometer. Theaccelerometer of the described invention can operate within anengineered magnetic environment. The accelerometer can be programmed tomeasure a specific type of movement. Deflections recorded by theaccelerometer can be registered into a processor and recognized byfirmware as being from a particular pre-specified activity by theengineered magnetic environment. The accelerometer of the describedinvention can be programmed to record certain types of motion by themagnetic prescribed for a certain activity. The accelerometer of thedescribed invention can be programmed to record certain motions (i.e.,deflections, counts, clicks) but to not record other motions (i.e.,deflections, counts, clicks). Based on this differential recordation ofmotion (i.e., programmed to record certain motions but not to recordother motions) by the accelerometer, differential multipliers can beassigned to different activities which reflect the different amount ofenergy required to perform different types of motion.

In an embodiment, the accelerometer of the described invention includesparameters of function. Such parameters include, but are not limited to,sensitivity, scale, detection time, count minimum and release time.

In an embodiment, the described invention allows a user to select thesite (e.g., wrist, pocket, ankle, lanyard, etc.) where the activitymodule will be worn. It is generally accepted that an accelerometer willcount with wide variation for the same activity (e.g., walking) if wornin different locations on the body. By allowing a user to choose thesite where the activity module will be worn, the activity module can beprogrammed to that particular body location so that the accelerometercan count the same number of deflections for an activity (e.g., walking)performed with the activity module, for example, worn in the lanyardposition, as for the same activity (e.g., walking) performed with theactivity module worn, for example, on the wrist.

According to the Centers for Disease Control and Prevention, anestimated 50-70 million U.S. adults suffer from a sleep or wakefulnessdisorder (Institute of Medicine. Sleep Disorders and Sleep Deprivation:An Unmet Public Health Problem. Washington, D.C.: The National AcademiesPress; 2006). Current methods for identifying sleep disorders are costlyand inconvenient. A sleep recording or polysomnogram (PSG) is performedovernight at a sleep center or sleep laboratory. Electrodes and othermonitors are placed on the scalp, face, chest, limbs and finger. Thesedevices measure brain activity, eye movement, muscle activity, heartrate and rhythm, blood pressure and oxygen levels in the lungs and bloodduring sleep.

In an embodiment, the described invention provides an activitymonitoring mode for sleep. By way of example, a user assigns a timeperiod in which the user is going to bed by activating a “going to bed”command on a device (e.g., mobile phone) containing a sleep algorithm ofthe described invention. The “going to bed” command can be transmittedto the activity module worn by the user via Bluetooth™. The processorreprograms the standard mode (“S”) by changing the parameters designedto capture motion of routine daily activities to parameters designed tocapture motion when lying in bed. Restfulness of the sleep period can bedetermined by tracking the amount of motion that occurs during theassigned time period by the motion sensor, e.g., accelerometer. The userthen declares a conclusion to this sleep period by activating a “gettingup” command on a device (e.g., mobile phone) containing a sleepalgorithm of the described invention. The “getting up” command can betransmitted to the activity module worn by the user via Bluetooth™. Theprocessor reprograms the standard mode (“S”) by changing the parametersdesigned to capture motion when lying in bed to parameters designed tocapture motion of routine daily activities. Because the motionassociated with sleep is not associated with other forms of activity,the motion sensor, e.g., accelerometer, data can be stored in a separatecounter from that used to store accelerometer data from other forms ofactivity. The motion sensor, e.g., accelerometer, data can be analyzedin comparison to other rest periods in order to create a portfolio ofuser movement during sleep time hours amortized for comparison intounits of motion per unit time in “going to bed” mode. By comparing thesemovements, the sleep algorithm of the described invention can track anddisplay weighted percentages of movement changes and determine howquiescent (i.e., restful) sleep was during the assigned time period.

In an embodiment, the described invention provides a method formeasuring quality of sleep (e.g., restfulness). By way of example, auser assigns a time period in which the user is going to bed byactivating a “going to bed” command on a device (e.g., mobile phone)containing a sleep algorithm of the described invention. The “going tobed” command can be transmitted to the activity module worn by the uservia Bluetooth™. The processor reprograms the standard mode (“S”) bychanging the parameters designed to capture motion of routine dailyactivities to parameters designed to capture motion when lying in bed.Restfulness of the sleep period can be determined by tracking the amountof motion (i.e., deflections, counts, clicks, etc.) that occurs duringthe assigned time period by the motion sensor, e.g., accelerometer. Theuser then declares a conclusion to this sleep period by activating a“getting up” command on a device (e.g., mobile phone) containing a sleepalgorithm of the described invention. The “getting up” command can betransmitted to the activity module worn by the user via Bluetooth™. Theprocessor reprograms the standard mode (“S”) by changing the parametersdesigned to capture motion when lying in bed to parameters designed tocapture motion of routine daily activities. Because the motionassociated with sleep is not associated with other forms of activity,the motion sensor, e.g., accelerometer, data can be stored in a separatecounter from that used to store accelerometer data from other forms ofactivity. The motion sensor, e.g., accelerometer, data can be analyzedin comparison to other rest periods in order to create a portfolio ofuser movement during sleep time hours amortized for comparison intounits of motion per unit time in “going to bed” mode. By comparing thesemovements, the sleep algorithm of the described invention can track anddisplay weighted percentages of movement changes and determine howquiescent (i.e., restful) sleep was during the assigned time period.Without being bound by theory, greater periods of decreased motion mayimply a more restful sleep.

In an embodiment, 0-400 accelerometer deflections per night can beindicative of restful sleep. In another embodiment, 50, 100, 150, 200,250, 300, 350 and 400 accelerometer deflections per night can beindicative of restful sleep.

In an embodiment, 400-600 accelerometer deflections per night can beindicative of less restful sleep. In another embodiment, 450, 500, 550and 600 accelerometer deflections per night can be indicative of lessrestful sleep.

In an embodiment, 600-1,000 accelerometer deflections per night can beindicative of a sleep disturbance. In another embodiment, 650, 700, 750,800, 850, 900, 950 and 1,000 accelerometer deflections per night can beindicative of a sleep disturbance. In another embodiment, sleepdisturbances include but are not limited to, sleep apnea.

In an embodiment, the described invention provides a method fordetermining an increased physiological benefit during sleep.

It is generally accepted that the glymphatic system, a brain-wideparavascular pathway for cerebrospinal fluid (CSF) and interstitialfluid (ISF) exchange, facilitates efficient clearance of solutes, wasteand proteins linked to neurodegenerative diseases from the brain (IliffJ. J. et al., The Journal of Clinical Investigation, Vol. 123, No. 3,March 2013, pp. 1299-1309; Iliff J. J., Science Translational Medicine,4, 147ra111 (2012); Yang L. et al., Journal of Translational Medicine2013 11:107). Proteins linked to neurodegenerative disease includeβ-amyloid (Aβ), α-synuclein and tau which are present in theinterstitial space surrounding cells of the brain (Id.). Xie et al.(Xie, L. et al., Science 342, 373 (2013)) have shown that natural sleepor anesthesia in mice is associated with a 60% increase in theinterstitial space, resulting in an increase in convective exchange ofCSF and ISF. In turn, these connective fluxes of the ISF increased therate of clearance of proteins linked to neurodegenerative disease (e.g.,Aβ) during sleep, leading Xie et al. to conclude that the restorativefunction of sleep may be a consequence of the enhanced removal ofpotentially neurotoxic waste products that accumulate in the awakecentral nervous system (Xie, L. et al., Science 342, 373 (2013)).

In an embodiment, the described invention can process sleep deflectionsinto the health quotient. Without being bound by theory, a decrease insleep deflections may be indicative of improved fitness while anincrease in sleep deflections may be indicative of a sleep disturbance.

In an embodiment, the described invention can set goals for the typesand amounts of activity to be performed. For example, a user accesseshis/her profile page and selects “Arc label” or “fitness program”. Onceselected, the program can analyze what percentage of activity should beresistance training, cardio training and routine activity for theprofile selected. This percentage goal for each type of activity isassigned to training circles. Therefore, the user's goal is to fill thetraining circle in order to meet the goals as determined on the user'sprofile page. These training circles are a percentage of activity (i.e.,not an absolute number). As the user varies activity (e.g., byperforming more exercise) there will be more deflections in the dailyactivity circle which represents the total number of activity counts forthe day. For example, more of any given type of exercise will need totake place to fill the muscle or cardio training circle completely. Thepercentage will remain constant, but the number of activity counts willgo up and down depending on the users overall pattern of activity. Theprogram examines the user's history and number of deflections recordedduring the day and then divides those deflections into various forms ofactivity (e.g., aerobic, routine, etc.) in order to meet the traininggoals selected on the user's profile page. A different profile willassign different percentages to the training circles. The total numberof deflections required to reach the user's selected fitness and weightgoals are determined by the program analytics based on changes in weightand muscle mass. The activity count goals are determined aftercalculation of the patients basic internal requirement needs (BIRN)which is the activity module's equivalent of metabolism. The programaccounts for age differences, gender differences, and beginning fitnesslevels not by assigning values based upon these characteristics, but byindividually studying the user's BIRN, exercise and food consumptionbehavior. In addition, the program has the ability to instantaneouslyreview the percentage of activity that is aerobic versus weight orresistance training. In another embodiment, the percentages in thetraining circles can be customized. For example, the percentages in thetraining circles can be changed and recalculated by an athletic trainerworking with a user.

FIG. 15A illustrates a band 118 that is depicted positioned adjacent tothe activity module 14. In an embodiment, the band 118 has a strap 120with a pouch or receptacle 122 that can be centrally positioned thereon.A magnet 123 can be embedded in the center of the receptacle 122, formagnetically retaining the activity module 14 in the receptacle 122. Thestrap 120 can have connectors 124, 126 that facilitate the releasablefastening of the strap 120 around the wrist or ankle of the user. Moreparticularly, a pin 124 may fasten on one of a plurality ofcircular-shaped pin-catches 126. Alternatively, the connectors 124, 126may be hook-and-loop fasteners such as Velcro®. The band 118 can befabricated from an elastomeric material, such as rubber. Also, the band118 may be formed as a bracelet, e.g., with a series of metal links thatcan be fastened about the wrist or ankle of the user.

In an embodiment, the strap 120 can be imprinted with an indicia A thatcan be located proximate to one side of the receptacle 122. The indiciaA can represent a user aerobic exercise mode. The strap 120 can be alsoimprinted with an indicia W that can be located proximate to theopposite side of the receptacle 122. The indicia W can represent a userweight training exercise mode. Imbedded in the strap 120, locatedproximate to the indicia A, can be a permanent magnet (not shown) whichcan have one of its magnetic poles directed toward the receptacle 122.Imbedded in the strap 120, located proximate to the indicia W can be apermanent magnet (not shown) which has an opposite magnetic poledirected toward the receptacle 122. Alternately, the activity module 14may be worn on a garment clip, in a pocket, on a lanyard, etc.

Referring to FIG. 15B, the activity module 14 is shown installed in thereceptacle 122. The receptacle 122 can be sized and shaped for removablyreceiving the activity module 14, and due to the supple nature of theelastomeric material construction of the receptacle 122, the activitymodule 14 may be installed in the receptacle 122 by way of the userpositioning one edge of the activity module 14 in the opening of thereceptacle 122 and pressing the opposite edge until it can be fullyinstalled in the receptacle 122. The activity module 14 may be removedfrom the receptacle 122 by pressing the exterior of the bottom of thereceptacle 122, towards the bottom 100 of the activity module 14, untilthe activity module 14 is pressed out of the receptacle 122. This mayserve to hold the activity module 14 within the receptacle 122 evenwithout the magnet 123. In an embodiment, due to the supple nature ofthe receptacle, the activity unit 14 may remain installed in thereceptacle 122 when the user simultaneously presses the buttons 104.

Referring to FIG. 16, the activity module 14 can include at least onemulti-axis accelerometer 128, or alternatively two or three single axisaccelerometers, an activity units counter 130, a daily counter 132, atime counter 134, e.g., a minutes counter 134, a Bluetooth™ transceiver136, a magnetic flux field sensor 138, and a processor/logic (computingdevice) unit 140. The multi-axis accelerometer 128 can be a tri-axisaccelerometer unit 128 that measures, e.g., the deflections of asuspended mass (not illustrated) in three orthogonal directions as aresult of movement of the activity module 14. For example, any change inthe movement of activity module 14 that is caused by changes in themovement of the user can cause an acceleration of the suspended mass inthe X, Y and/or Z axis of the accelerometer 128, resulting in adeflection or “click” of the accelerometer 128 in X, Y or Z axis. Eachsuch deflection can be used to produce one click, which can be equatedto an activity unit or a portion of an activity unit, by theprocessor/logic unit 140 of the activity module 14, or alternatively, insome modes, two “clicks”, one forward and one back, can be equated to anactivity unit or a portion of an activity unit, in a manner discussedbelow. The activity units can be recorded and accumulated in theactivity counter 130 and/or the daily counter 132, and can betransmitted (i.e., downloaded) to the application 12, e.g., by theBluetooth™ transceiver 136, periodically and/or during thesynchronization process that is described above. The activity units canbe processed by the power equation 2, as described above.

The activity counter 130 can keep a running total of the activity units,e.g., until it receives a command from the digital device D. This datacan be maintained for additional analysis, e.g., in the event that theuser fails to download activity from the daily counter 132 which, e.g.,may be configured to reset to zero every 24 hours, or to separatelystore daily accumulations for several days. The activity counter 130 canalso start to count until it reaches the maximum value allowed by thehardware. At that time, it can be reset to zero. It can be, therefore,possible that the activity counter 130 may keep counting on multipledays. It will be understood that the user may command the application 12to reset the activity counter 130 to zero by using a “clear activity”command (not shown) during synchronization between the digital device Dand the activity module 14.

The daily counter 132 can maintain a running total of activity units fora 24 hours period(s). With each synchronization the application 12 canthen calculate the difference between the last and current activitycount for a given 24 hour period in order to update calculations andpage displays. For example, the application 12 can update the activitycircle 38 count and the expected number of activity units on theactivity module 14. Therefore, the daily counter 132 can start to countactivity units until the end of the day (i.e., when the minute timer 134reaches a value of 1440 minutes) at which time it can be reset to zero.It will be understood that the application 12 can remember the dailycounter's 132 value at the last synchronization so that the applicationcan calculate the difference in the recorded values betweensynchronizations.

Since it can be possible that the activity unit 14 might not be in syncwith the current time (at the minute level) during synchronization, thedigital device D can set the minute timer 134 to the current time basedon the digital device's D clock. This can assure that the application 12and the activity module 14 both conclude a 24 hour (i.e., 1440 minute)period at the same time and can allow the user to travel to differenttime zones and maintain accurate application 12 functionality. At theend of the daily 1440 minute countdown, the activity module 14 can resetand begin a new count which can correspond to the next day.

The user can adjust the activity module 14 to measure an aerobic mode ofexercise, or an anaerobic, e.g., weight training, mode of exercise. Thiscan be accomplished by orienting the activity module 14 in thereceptacle 122 of the band 118 so that when the arrow-shaped pointer 106is pointing to the indicia A, the orientation of the magnetic flux fieldexerted by the strap 120 can be detected by the magnetic flux fieldsensor 138 and can be communicated to the processor/logic unit 140. Theprocessor/logic unit 140 can then interpret the activity units as beinggenerated by the user who is performing aerobic exercise. When the userorients the activity module 14 in the receptacle 122 so that thearrow-shaped pointer 106 points to the indicia W, the processor/logicunit 140 can interpret the output of the magnetic flux detector 138 asindicating the user activity units are being generated by the user whois performing some form of anaerobic exercise, e.g., weight lifting.When so oriented, the processor/logic unit 86 of the activity module 14can add a multiplier to the calculations of the activity count. (Themultiplier number may be changed via an input to the algorithm throughthe Bluetooth™ interface). The multiplier can alter the activity countsthat can be transmitted to the application 12, so that each individualdeflection (or back and forth deflection) may be transmitted to theapplication 12 as a single count, e.g., in a normal anaerobic trainingmode, or “standard activity” mode or, for example, multiplied by 2 forintense anaerobic training, or multiplied by 3 for aerobic training, orby 4 for intense aerobic training. It will be understood that othermultipliers and/or means of accounting for a single step or singleexercise repetition, or the like, may be possible

When the user is about to begin high intensity or “turbo” exerciseactivities, he/she can briefly depress the buttons 104. This can, e.g.,place the activity module 14 temporarily in a high intensity or turbophysical exercise monitoring mode in which the activity units that aregenerated by the activity module 14 can be multiplied by an additionalfactor so that each deflection has a greater impact on the activitycircle 116 than when in (“normal”) weight training or aerobic trainingwithout the turbo function engaged. An indicator light 119 may beilluminated when the activity module 14 can be placed in the turboexercise monitoring mode. At the end of the turbo exercise activitiesthe user can again briefly depress the buttons 104 to exit the highintensity exercise mode, or alternately, the activity module 14 canautomatically turn off the high intensity exercise monitoring mode whenit senses a sustained decrease in the frequency of activity units.

As described above, the activity module 14 can be adapted to measure andrecord activity units in the following five physical activity modes: i)aerobic, ii) intense or turbo aerobic, iii) weight or muscle training,iv) intense or turbo weight training, and v) standard activity mode. Theprocessor/logic unit 140 can, e.g., interpret one click of theaccelerometer in each of the five physical activity modes as follows: i)in the aerobic exercise mode, one click can be equal to (A×1 repetition)activity unit, where A can be a predetermined constant coefficient, ii)in the turbo aerobic mode, one click can be equal to (A+×1 repetition)activity unit, where A+ can be a predetermined coefficient, iii) in theweight training mode, one click can be equal to (W×1 repetition)activity unit, where W can be a predetermined coefficient, iv) in theturbo weight training mode, one click can be equal to (W+×1 repetition)activity unit, where W+ can be a predetermined coefficient, and v) inthe standard activity mode, one click can be equal to (R×1 repetition oralternatively time period) activity unit, where R can be a predeterminedconstant coefficient. These values can be altered, e.g., via theBluetooth™ algorithm by the user, athletic coach or health professionalto create unique exercise programs beyond those provide in the system10.

It should be appreciated that the disclosed subject matter providesnumerous advantages. For instance, in the event that the application 12is implemented on a digital device D such as a smart phone, the system10 can be therefore normally close at hand to the user throughout theday. This can encourage the user to accurately input food consumptionclose to the time it occurs. The method of utilizing food icons forinputting the type and portion size for food consumption, without theneed for looking up and computing calories, can further encourage theuser to more accurately and conveniently input food consumption and todo so close to the time it is or will be consumed. Likewise, wearing theactivity module 14 can further contribute to the user conveniently andautonomously inputting the activity units in the systems 10. The system10 features concise, powerful and completing graphical indicators on thehealth and fitness of the user, such as i) the fitness arc 34 which canprovide, e.g., an energy balance that can be an indicator of theeffectiveness of the user's daily weight and fitness management, ii) thehealth quotient 42 which can provide, e.g., an indicator of the healthof the user for a particular extended time period, iii) the fluid ansalt circles 31A and 31B, iv) the activity circle 38, the v) the Vitcircle 82, and the like and vi) favorite food indicator(s) 56. Further,the system 10 can compensate(s) for user inaccuracies in food portionsize estimates by assessing the user's energy balance including his/herintrinsic metabolism and adjusting the food estimates accordingly orsimply automatically increasing or decreasing the food intake units,e.g., daily. The system also has the flexibly of operating on a combinedmode, or an estimated mode in which the user does not utilize theactivity module 14, and instead estimates his/her activity units.

For example, the estimated algorithm mode of the application 12 canbegin with an assigned and fixed number of activity units. The assignedamount can be derived from the learning algorithm that runs when theactivity module 14 is actually used to record all activity, or in caseswhere the activity module 14 has not been used, a value can be assignedbased upon the users selected profile.

Referring to FIG. 17, the user can make a selection from an estimatedactivity page 142 that describes his/her activity. The entry of theestimated amount of activity can be input as often as the user chooses.If no entries are made, the algorithm can assume that the activity forthat day was a usual or forecasted/assigned amount, or the like. Eachuser estimated activity update can apply to the time period from thelast entry/estimation. Thus if 100 activity units were expected at 8 AMand the user selects “usual,” then 100 units can be added to activitycircle 116. Selection of a plus or minus option can alter the activityunits forecasted/assigned for that period of time by plus or minus 10%,20% or 30%. For example, the activity units entered might be 100, 120 or80 etc.

The next time the user enters the estimated activity, the application 12can have expected a certain number of activity units to have beenperformed since the last entry. Expected activity units can be thenumber registered to the activity circle if the user selects the “usual”option from the estimated activity page 142. The number of expectedunits can be determined by the amount of time that has past, since theuser last registered activity by a selection from the estimated activitypage 142. For example the algorithm might have expected the user to haveregistered 1000 activity units since the time of last entry, and if“+++” is selected, the algorithm can place 1300 units into the activitycircle 116. If at the time of the next entry 2000 units would have beenexpected (i.e., 2,000 units would have occurred in the time frame sincethe last entry) and “−−” had been selected, the algorithm can enter1,600 units into the activity circle 116.

If the estimated activity units are used to describe the majority ofdaily activity, but the user wishes to use the activity module 14 toquantify exercise, then the application 12 can process those activityunits as a percentage of those expected during the time frame duringwhich activity module 14 was in use and apply a 10%, 20%, or 30%increment to the activity count total. For example, if in the time framebetween the last entry in the application 12 estimation-algorithm'salgorithm the algorithm would expect 1000 units, but the user, insteadof making a selection from the estimated activity page chooses toutilize the activity module 14 for entry of actual activity units, thealgorithm can perform as follows:

for any number of activity units that the activity module 14 provideswhich are less than expected plus 20% (1200 activity units in thecurrent example) the application can place the expected plus 10% unitsinto the activity circle 116, (1100 activity units in the currentexample); between an expected plus 20% and expected plus 30% theapplication 12 can add expected plus 20% to activity circle 116, (1200units in the current example); and for any number of activity unitsabove 30% of expected, then the expected plus 30% can be added toactivity circle 116, (1300 units in the current example). The maximumallowed activity count can be an expected plus 30%, regardless of theactual number of activity counts (e.g., 1400 activity units would beentered as 1300 units to activity circle 116).

It should be noted that the disclosed subject matter can have numerousmodifications and variations. For instance, users sponsored by abusiness or organization may receive downloads to the system 10. Thebusiness or organization may generate a rewards algorithm for thesponsored users by providing benefits such as financial rewards, music,cell phone minutes, video game access, etc.

In some embodiments, the device D may receive signals not only from anactivity module 14, but also from other devices. For example, a bodyweight scale may be adapted to wirelessly transmit weight values to thedigital device D, thereby automatically recording the user's actualweight in the system 10. In another embodiment, the body weight scalecan be used to confirm calculations relating to the user's weight. Forexample, the user's actual weight is transmitted to the device D viaBluetooth™. The transmitted actual weight is used to validatecalculations relating to the user's weight. The user does not see anactual numeric value on the device or on the body weight scale.

In an embodiment of the method in step (e), the change in weight isdisplayable either as a numeric weight or via a colored dot displaysystem, the colored dot display system comprising: a red dotrepresenting weight gain other than muscle; a green dot representingmuscle growth or weight loss; and a yellow dot representing no change infat/muscle ratios.

It is generally accepted that weight is not a perfect surrogate forhealth or fitness. Weight can be altered by total body fluid, body wasteaccumulation or loss, as well as muscle mass gains and losses. It isunderstood that these components do not equate to or have the sameimplications as to health status as does fat or adipose tissue changes.In addition, psychological management benefits are associated with aweightless program. For example, some individuals have a phobia aboutmeasured weight and do not wish or cannot step on a scale. The inabilityto measure weight can be an obstacle in collecting data about anindividual's health and the appropriateness of food consumption.

According to the described invention, multiple algorithms can be used toassess whether weight is gained from fat, water or muscle. Thealgorithms can review and assess types and amounts of food consumed,amount of liquids and salt consumed, as well as exercised performed andthe rate of change in weight. By way of example, if a user consumes only⅔ of his/her usual food allowance and performed 20% more exercise, yetthe next day gained ½ pound, the software of the described invention canstudy these relationships and assign a value to the user's healthquotient which reflects a true meaning of the measured weight. Forexample, foods consumed may have had a very high salt content whichadded to water retention thus increasing weight. The software of thedescribed invention can determine whether change in weight is meaningfulas a health determinant (i.e., from fat, water or muscle mass) and thusassign a color to represent whether a desired, neutral or undesiredchanged in weight has occurred. For example, a yellow circle can beassigned to indicate no meaningful fitness or health change to a user'sweight. A red circle, for example, can be assigned to indicate thatthere has been weight gain which falls outside of the users statedhealth goals. A green circle, for example, can indicate that there hasbeen weight loss in accordance with the user's health goals. Thus, theweightless fitness management program of the described inventionprovides the use of a color in place of a numerical weight value.

Some users wish to gain weight for health and fitness purposes, but notall weight gain is healthy. The weightless fitness management program ofthe described invention can perform an assessment of food amount andtype, as well as the amount and type of activity performed (e.g.,anaerobic weight lifting versus aerobic jogging). This assessment candetermine if changes in weight are the result of proper eating andtraining effort. Once the determination is made, a color as describedabove is displayed in place of numerical weight. The weightless fitnessmanagement program of the described invention can distinguish whetherweight gain is muscle or fat based on the types and amount of exerciseperformed.

In an embodiment, the data used by the weightless fitness managementprogram to determine whether weight gain is muscle or fat can beintegrated into the multiple parameters that form the health quotient ofthe described invention and thus displayed as a single point on a scaleranging from fit to healthy to unhealthy to at risk.

Similarly, when test results items such as blood pressure are recorded,such information may be automatically transmitted to the digital deviceD. In other embodiments, the digital device D may interface with anelectronic patient chart, allowing the user to upload information fromthe user medical chart directly to the system 10. In an embodiment, thesystem 10 may provide real time advice with respect to the user's choiceof foods and activity to improve the prospect of reaching specifichealth and fitness goals, and the system 10 may consider factors such aswhether the user is a long distance runner, whether the user ispregnant, elderly, and/or whether the user has health related diseasessuch as hypertension, diabetes, obesity, or anorexia. Having disclosedthe apparatus and functions of the system 10, examples of some of thesystem 10 operational facilities are provided below.

Referring to FIG. 18, the user may reprogram the activity module 14(e.g., the activity monitoring modes described herein), e.g., via theapplication 10 and the Bluetooth™ transceiver of the digital device D.Also FIGS. 19A and 19B illustrate a facility to remove a day's input,which may be required should the user believe that data for a particularday are not correct or was not entered accurately.

The following is a disclosure by way of example of a computing devicewhich may be used with the presently disclosed subject matter. Thedescription of the various components of a computing device is notintended to represent any particular architecture or manner ofinterconnecting the components. Other systems that have fewer or morecomponents may also be used with the disclosed subject matter. Acommunication device may constitute a form of a computing device and mayat least emulate a computing device. The computing device may include aninter-connect (e.g., bus and system core logic), which can interconnectsuch components of a computing device to a data processing device, suchas a processor(s) or microprocessor(s), or other form of partly orcompletely programmable or pre-programmed device, e.g., hard wiredand/or application specific integrated circuit (“ASIC”) customized logiccircuitry, such as a controller or microcontroller, a digital signalprocessor, or any other form of device that can fetch instructions,operate on pre-loaded/pre-programmed instructions, and/or followinstructions found in hardwired or customized circuitry, to carry outlogic operations that, together, perform steps of and whole processesand functionalities as described in the present disclosure.

In this description, various functions, functionalities and/oroperations may be described as being performed by or caused by softwareprogram code to simplify description. However, those skilled in the artwill recognize what is meant by such expressions is that the functionsresulting from execution of the program code/instructions are performedby a computing device as described above, e.g., including a processor,such as a microprocessor, microcontroller, logic circuit or the like.Alternatively, or in combination, the functions and operations can beimplemented using special purpose circuitry, with or without softwareinstructions, such as using Application-Specific Integrated Circuit(ASIC) or Field-Programmable Gate Array (FPGA), which may beprogrammable, partly programmable or hard wired. The applicationspecific integrated circuit (“ASIC”) logic may be such as gate arrays orstandard cells, or the like, implementing customized logic bymetalization(s) interconnects of the base gate array ASIC architectureor selecting and providing metalization(s) interconnects betweenstandard cell functional blocks included in a manufacturer's library offunctional blocks, etc. Embodiments can thus be implemented usinghardwired circuitry without program software code/instructions, or incombination with circuitry using programmed software code/instructions.

Thus, the techniques are limited neither to any specific combination ofhardware circuitry and software, nor to any particular tangible sourcefor the instructions executed by the data processor(s) within thecomputing device. While some embodiments can be implemented in fullyfunctioning computers and computer systems, various embodiments arecapable of being distributed as a computing device including, e.g., avariety of forms and capable of being applied regardless of theparticular type of machine or tangible computer-readable media used toactually effect the performance of the functions and operations and/orthe distribution of the performance of the functions, functionalitiesand/or operations.

The inter-connect may connect the data processing device to define logiccircuitry including memory. The interconnect may be internal to the dataprocessing device, such as coupling a microprocessor to on-board cachememory, or external (to the microprocessor) memory such as main memory,or a disk drive, or external to the computing device, such as a remotememory, a disc farm or other mass storage device(s), etc. Commerciallyavailable microprocessors, one or more of which could be a computingdevice or part of a computing device, include a PA-RISC seriesmicroprocessor from Hewlett-Packard Company, an 80×86 or Pentium seriesmicroprocessor from Intel Corporation, a PowerPC microprocessor fromIBM, a Sparc microprocessor from Sun Microsystems, Inc, or a 68xxxseries microprocessor from Motorola Corporation as examples.

The inter-connect in addition to interconnecting such asmicroprocessor(s) and memory may also interconnect such elements to adisplay controller and display device, and/or to other peripheraldevices such as input/output (I/O) devices, e.g., through aninput/output controller(s). Typical I/O devices can include a mouse, akeyboard(s), a modem(s), a network interface(s), printers, scanners,video cameras and other devices which are well known in the art. Theinter-connect may include one or more buses connected to one anotherthrough various bridges, controllers and/or adapters. In one embodimentthe I/O controller may include a USB (Universal Serial Bus) adapter forcontrolling USB peripherals, and/or an IEEE-1394 bus adapter forcontrolling IEEE-1394 peripherals.

The memory may include any tangible computer-readable media, which mayinclude but are not limited to recordable and non-recordable type mediasuch as volatile and non-volatile memory devices, such as volatile RAM(Random Access Memory), typically implemented as dynamic RAM (DRAM)which requires power continually in order to refresh or maintain thedata in the memory, and non-volatile ROM (Read Only Memory), and othertypes of non-volatile memory, such as a hard drive, flash memory,detachable memory stick, etc. Non-volatile memory typically may includea magnetic hard drive, a magnetic optical drive, or an optical drive(e.g., a DVD ROM, a CD ROM, a DVD or a CD), or other type of memorysystem which maintains data even after power is removed from the system.

A server could be made up of one or more computing devices. Servers canbe utilized, e.g., in a network to host a network database, computenecessary variables and information from information in the database(s),store and recover information from the database(s), track informationand variables, provide interfaces for uploading and downloadinginformation and variables, and/or sort or otherwise manipulateinformation and data from the database(s). In one embodiment a servercan be used in conjunction with other computing devices positionedlocally or remotely to perform certain calculations and other functionsas may be mentioned in the present application.

At least some aspects of the disclosed subject matter can be embodied,at least in part, utilizing programmed software code/instructions. Thatis, the functions, functionalities and/or operations techniques may becarried out in a computing device or other data processing system inresponse to its processor, such as a microprocessor, executing sequencesof instructions contained in a memory, such as ROM, volatile RAM,non-volatile memory, cache or a remote storage device. In general, theroutines executed to implement the embodiments of the disclosed subjectmatter may be implemented as part of an operating system or a specificapplication, component, program, object, module or sequence ofinstructions usually referred to as “computer programs,” or “software.”The computer programs typically comprise instructions stored at varioustimes in various tangible memory and storage devices in a computingdevice, such as in cache memory, main memory, internal or external diskdrives, and other remote storage devices, such as a disc farm, and whenread and executed by a processor(s) in the computing device, cause thecomputing device to perform a method(s), e.g., process and operationsteps to execute an element(s) as part of some aspect(s) of themethod(s) of the disclosed subject matter.

A tangible machine readable medium can be used to store software anddata that, when executed by a computing device, causes the computingdevice to perform a method(s) as may be recited in one or moreaccompanying claims defining the disclosed subject matter. The tangiblemachine readable medium may include storage of the executable softwareprogram code/instructions and data in various tangible locations,including for example ROM, volatile RAM, non-volatile memory and/orcache. Portions of this program software code/instructions and/or datamay be stored in any one of these storage devices. Further, the programsoftware code/instructions can be obtained from remote storage,including, e.g., through centralized servers or peer to peer networksand the like. Different portions of the software programcode/instructions and data can be obtained at different times and indifferent communication sessions or in a same communication session.

The software program code/instructions and data can be obtained in theirentirety prior to the execution of a respective software application bythe computing device. Alternatively, portions of the software programcode/instructions and data can be obtained dynamically, e.g., just intime, when needed for execution. Alternatively, some combination ofthese ways of obtaining the software program code/instructions and datamay occur, e.g., for different applications, components, programs,objects, modules, routines or other sequences of instructions ororganization of sequences of instructions, by way of example. Thus, itis not required that the data and instructions be on a single machinereadable medium in entirety at any particular instant of time.

In general, a tangible machine readable medium includes any tangiblemechanism that provides (i.e., stores) information in a form accessibleby a machine (i.e., a computing device), which may be included, e.g., ina communication device, a network device, a personal digital assistant,a mobile communication device, whether or not able to download and runapplications from the communication network, such as the Internet, e.g.,an I-Phone®, Blackberry®, Droid™ or the like, a manufacturing tool, orany other device including a computing device, comprising one or moredata processors, etc.

In one embodiment, a user terminal can be a computing device, such as inthe form of or included within a PDA, a cellular phone, a notebookcomputer, a personal desktop computer, etc. Alternatively, thetraditional communication client(s) may be used in some embodiments ofthe disclosed subject matter.

While some embodiments of the disclosed subject matter have beendescribed in the context of fully functioning computing devices andcomputing systems, those skilled in the art will appreciate that variousembodiments of the disclosed subject matter are capable of beingdistributed, e.g., as a program product in a variety of forms and arecapable of being applied regardless of the particular type of computingdevice machine or computer-readable media used to actually effect thedistribution.

The disclosed subject matter may be described with reference to blockdiagrams and operational illustrations of methods and devices to providea system and methods according to the disclosed subject matter. It willbe understood that each block of a block diagram or other operationalillustration (herein collectively, “block diagram”), and combination ofblocks in a block diagram, can be implemented by means of analog ordigital hardware and computer program instructions. These computingdevice software program code/instructions can be provided to thecomputing device such that the instructions, when executed by thecomputing device, e.g., on a processor within the computing device orother data processing apparatus, the program software code/instructionscause the computing device to perform functions, functionalities andoperations of a method(s) according to the disclosed subject matter, asrecited in the accompanying claims, with such functions, functionalitiesand operations specified in the block diagram.

It will be understood that in some possible alternate implementations,the function, functionalities and operations noted in the blocks of ablock diagram may occur out of the order noted in the block diagram. Forexample, the function noted in two blocks shown in succession can infact be executed substantially concurrently or the functions noted inblocks can sometimes be executed in the reverse order, depending uponthe function, functionalities and operations involved. Therefore, theembodiments of methods presented and described as a flowchart(s) in theform of a block diagram in the present application are provided by wayof example in order to provide a more complete understanding of thedisclosed subject matter. The disclosed flow and concomitantly themethod(s) performed as recited in the accompanying claims are notlimited to the functions, functionalities and operations illustrated inthe block diagram and/or logical flow presented herein. Alternativeembodiments are contemplated in which the order of the variousfunctions, functionalities and operations may be altered and in whichsub-operations described as being part of a larger operation may beperformed independently or performed differently than illustrated or notperformed at all.

Although some of the drawings may illustrate a number of operations in aparticular order, functions, functionalities and/or operations which arenot now known to be order dependent, or become understood to not beorder dependent, may be reordered and other operations may be combinedor broken out. While some reordering or other groupings may have beenspecifically mentioned in the present application, others will be or maybecome apparent to those of ordinary skill in the art and so thedisclosed subject matter does not present an exhaustive list ofalternatives. It should also be recognized that the aspects of thedisclosed subject matter may be implemented in parallel or seriatim inhardware, firmware, software or any combination(s) thereof co-located orremotely located, at least in part, from each other, e.g., in arrays ornetworks of computing devices, over interconnected networks, includingthe Internet, and the like.

The disclosed subject matter is described in the present applicationwith reference to one or more specific exemplary embodiments thereof.Such embodiments are provided by way of example only. It will be evidentthat various modifications may be made to the disclosed subject matterwithout departing from the broader spirit and scope of the disclosedsubject matter as set forth in the appended claims. The specificationand drawings are, accordingly, to be regarded in an illustrative sensefor explanation of aspects of the disclosed subject matter rather than arestrictive or limiting sense. Numerous variations, changes, andsubstitutions will now occur to those skilled in the art withoutdeparting from the disclosed subject matter. It should be understoodthat various alternatives to the embodiments of the disclosed subjectmatter described herein may be employed in practicing the disclosedsubject matter. It is intended that the following claims define thescope of the disclosed subject matter and that methods and structureswithin the scope of these claims and their equivalents be coveredthereby.

It will be understood that the disclosed subject matter may comprise afitness management method and apparatus which may comprise collectingfood intake information for actual or expected food intake of a userover a first period of time and converting the food intake informationinto food intake units for the first period of time; collecting activityinformation for actual or expected activity by the user over the firstperiod of time and converting the food intake information into foodintake units for the user for the first period of time; collectingweight information representing a change in weight of the user over thefirst period of time; calculating, via a computing device, a calculatedintrinsic metabolic rate for the user for the first period of time;collecting food intake information for actual or expected food intake ofa user over a second period of time and converting the food intakeinformation into food intake units for the second period of time;collecting activity information for actual or expected activity of auser over the second period of time and converting the activityinformation into activity units for the second period of time;calculating, via the computing device, a predicted change in weight forthe second period of time based upon the calculated intrinsic metabolicrate for the user over the first period of time; collecting weightinformation representing an actual change in weight of the user over thesecond period of time; comparing the predicted change in weight for thesecond period of time to the actual change in weight for the secondperiod of time; determining, via the computing device, an updatedcalculated intrinsic metabolic rate for the user based at least in partupon the difference between the predicted change in weight for thesecond period of time and the actual change in weight for the secondperiod of time. The method and apparatus may further comprise collectingfood intake information for actual or expected food intake of a userover a third period of time and converting the food intake informationinto food intake units for the third period of time; collecting activityinformation for actual or expected activity of a user over the thirdperiod of time and converting the activity information into activityunits for the third period of time; calculating, via the computingdevice, a predicted change in weight for the third period of time basedupon the updated calculated intrinsic metabolic rate for the user overthe first period of time; collecting weight information representing anactual change in weight of the user over the second period of time;further updating, via the computing device, the updated calculatedintrinsic metabolic rate for the user based at least in part upon thedifference between the predicted change in weight for the third periodof time and the actual change in weight for the third period of time.The method and apparatus may further comprise: displaying, via thecomputing device, at least one of an accumulation of food intake unitsand an accumulation of activity units over at least one of the firstperiod of time, the second period of time and the third period of time.The apparatus and method may further comprise dividing the first periodof time into a selected number of first sub-time periods; collectingfood intake information for actual or expected food intake of the userover each of the first sub-time periods during the first period of timeand converting the food intake information into food intake units foreach of the first sub-time units during the first period of time;collecting activity information for actual or expected activity by theuser over each of the first sub-time periods and converting the activityinformation into activity units for the user for each of the sub-timeperiods during the first period of time; collecting weight informationrepresenting a change in weight of the user over at least a last of thefirst sub-time periods and a first of the first sub-time periods todetermine a change in weight of the user over the first period of time;dividing the second period of time into a selected number of secondsub-time periods; collecting food intake information for actual orexpected food intake of the user over each of the second sub-timeperiods during the second period of time and converting the food intakeinformation into food intake units for each of the second sub-time unitsduring the second period of time; collecting activity information foractual or expected activity by the user over each of the second sub-timeperiods and converting the activity information into activity units forthe user for each of the second sub-time periods during the secondperiod of time; collecting weight information representing a change inweight of the user over at least a last of the second sub-time periodsto determine a change in weight of the user over the second period oftime. The method and apparatus may further comprise dividing the thirdperiod of time into a selected number of third sub-time periods;collecting food intake information for actual or expected food intake ofthe user over each of the third sub-time periods during the third periodof time and converting the food intake information into food intakeunits for each of the third sub-time periods during the third period oftime; collecting activity information for actual or expected activity bythe user over each of the third sub-time periods and converting theactivity information into activity units for the user for each of thethird sub-time periods during the third period of time; and collectingweight information representing a change in weight of the user over atleast a last of the third sub-time periods to determine a change inweight of the user over the third period of time. The method andapparatus may further comprise determining an updated calculatedintrinsic metabolic rate for the user based at least in part upon thedifference between the predicted change in weight for the second periodof time and the actual change in weight for the second period of timeand determining a further updated calculated intrinsic metabolic ratefor the user based at least in part upon the difference between thepredicted change in weight for the second period of time and the actualchange in weight for the second period of time. A machine readablemedium storing instructions that, when executed by a computing devicecause the computing device to perform a fitness management method isdisclosed in which the method may comprising collecting food intakeinformation for actual or expected food intake of a user over a firstperiod of time and converting the food intake information into foodintake units for the first period of time; collecting activityinformation for actual or expected activity by the user over the firstperiod of time and converting the food intake information into foodintake units for the user for the first period of time; collectingweight information representing a change in weight of the user over thefirst period of time; calculating a calculated intrinsic metabolic ratefor the user for the first period of time; collecting food intakeinformation for actual or expected food intake of a user over a secondperiod of time and converting the food intake information into foodintake units for the second period of time; collecting activityinformation for actual or expected activity of a user over the secondperiod of time and converting the activity information into activityunits for the second period of time; calculating a predicted change inweight for the second period of time based upon the calculated intrinsicmetabolic rate for the user over the first period of time; collectingweight information representing an actual change in weight of the userover the second period of time; comparing the predicted change in weightfor the second period of time to the actual change in weight for thesecond period of time; determining an updated calculated intrinsicmetabolic rate for the user based at least in part upon the differencebetween the predicted change in weight for the second period of time andthe actual change in weight for the second period of time.

The system and method may comprise a food intake information and weightinformation input unit; an activity information collection and inputunit separate from the food intake information and weight informationinput unit and adapted to move with a portion a body of the user. Atleast one of the food intake information and weight information inputunit and the activity information collection and input may comprise thecomputing device. The system and method may comprise the foodinformation and weight information input unit comprising a portable userdevice having a touch screen display. The system and method may comprisethe activity information input unit comprising an accelerometer fordetecting activity repetitions. At least one of the food intakeinformation and weight information input unit and the activity inputunit the computing device may be configured to assign weighted values toeach activity repetition according to one of the type and intensity ofthe activity and at least one of the repetitions detected. The systemand method may comprise the food intake information input and weightinformation input unit further comprising the computing deviceconfigured to display a prediction of fitness performance based at leastin part on a current metabolic rate for the user. The current metabolicrate may be computed by the computing device based on a differencebetween a predicted change in weight for a selected period of time andan actual measured change in weight for the selected period of time. Thedisplayed prediction may comprise a graphical fitness prediction chartincluding perhaps a graphical fitness prediction chart.

Where a range of values is provided, it is understood that eachintervening value, to the tenth of the unit of the lower limit unlessthe context clearly dictates otherwise, between the upper and lowerlimit of that range and any other stated or intervening value in thatstated range is encompassed within the invention. The upper and lowerlimits of these smaller ranges which may independently be included inthe smaller ranges is also encompassed within the invention, subject toany specifically excluded limit in the stated range. Where the statedrange includes one or both of the limits, ranges excluding either bothof those included limits are also included in the invention.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention belongs. Although any methods andmaterials similar or equivalent to those described herein can also beused in the practice or testing of the present invention, exemplarymethods and materials have been described. All publications mentionedherein are incorporated herein by reference to disclose and describedthe methods and/or materials in connection with which the publicationsare cited.

It must be noted that as used herein and in the appended claims, thesingular forms “a”, “and”, and “the” include plural references unlessthe context clearly dictates otherwise.

The publications discussed herein are provided solely for theirdisclosure prior to the filing date of the present application and eachis incorporated by reference in its entirety. Nothing herein is to beconstrued as an admission that the present invention is not entitled toantedate such publication by virtue of prior invention. Further, thedates of publication provided may be different from the actualpublication dates which may need to be independently confirmed.

EXAMPLES

The following examples are put forth so as to provide those of ordinaryskill in the art with a complete disclosure and description of how tomake and use the present invention, and are not intended to limit thescope of what the inventors regard as their invention nor are theyintended to represent that the experiments below are all or the onlyexperiments performed. Efforts have been made to ensure accuracy withrespect to numbers used (e.g. amounts, temperature, etc.) but someexperimental errors and deviations should be accounted for. Unlessindicated otherwise, parts are parts by weight, molecular weight isweight average molecular weight, temperature is in degrees Centigrade,and pressure is at or near atmospheric.

Example 1 Determination of Quality of Sleep

For the first two weeks of use, the program associated with the sleepactivity monitoring mode counts how many movements there are during the“going to bed” period. A plot of the ratio of expected versus observednumber of counts is generated, and is displayed as a percentage ofexpected versus observed on the sleep Arc. The percentages are weightedto exclude variances that could be explained by transient events suchthat outlier observations are excluded from the calculations of the Arccalculations. The counts are weighted by an algorithm such that moremovement does not affect the Arc as much as less movement. This is basedupon studies of sleep and non-sleep associated movements and theirimplications in assessing the restfulness of the “going to bed” period.

During the first two weeks, it is not known what number of countsrepresent a restful or agitated “going to bed” period for a particularuser because reference data, other than that collected by the describedinvention (i.e., number of counts recorded on average for a particularuser) is not known. The program associated with the sleep activitymonitoring mode then looks for variance in the number of counts. Withoutbeing bound by theory, more counts would be indicative of a less restful“going to bed” period, while fewer counts would be indicative of a morerestful “going to bed” period.

When a particular user selects the sleep activity monitoring mode, thedirectionality in the number of counts is tracked, recorded and comparedto the fitness and health score in the Health Quotient. Without beingbound by theory, it is believed that as the Health Quotient improvesinto the healthy zone or the fit zone, the “going to bed” period shouldbecome more restful. If the “going to bed” period does not become morerestful, it may be indicative of a sleep dysfunction. The programassociated with the sleep activity mode will announce to the particularuser that there is a possible sleep disturbance. This assessment isderived from an analysis of the particular user's ‘going to bed” countsreferenced against the user's individual Heath Quotient.

The described invention is also able to determine the effect of theamount and types of exercise, caffeine, alcohol and food choices on therestfulness of a particular user's “going to bed” period. Thesebehaviors are time stamped to further indicate their effects, giventheir proximity to the user's “going to bed” period. The user can querythe program to search for the known triggers of a less restful “going tobed” period.

Without being bound by theory, the number and pattern of counts recordedin the sleep activity mode may be used in the actual diagnosis of asleep disorder. For example, night terrors may have episodic but aprolonged number of counts with each episode; sleep apnea may be briefbut frequent episodes of increased movement distributed equally throughthe night; restless leg syndrome activity may be of high volume butshort durations sporadically through the night.

While the present invention has been described with reference to thespecific embodiments thereof it should be understood by those skilled inthe art that various changes may be made and equivalents may besubstituted without departing from the true spirit and scope of theinvention. In addition, many modifications may be made to adopt aparticular situation, material, composition of matter, process, processstep or steps, to the objective spirit and scope of the presentinvention. All such modifications are intended to be within the scope ofthe claims appended hereto.

What is claimed is:
 1. A method for instantaneously and continuouslyassessing real time energy balance for fitness management comprising, inorder: (a) collecting food intake information for actual or expectedfood intake of a user over a specified period of time andcontemporaneously converting the food intake information into foodintake energy units for the first period of time, wherein the foodintake units are based on relative energy content of one food comparedto another without relying on standard caloric values; (b) collecting bya device activity information for actual or expected activity by theuser over the specified period of time and contemporaneously convertingthe activity information into energy units for the user for the firstperiod of time, wherein the collecting for actual activity is achievedby wireless transmission by a motion sensor and the motion sensor is aprogrammable accelerometer, the functional status of which is alteredby: (i) programming independent of a magnetic field; (ii) collectingdeflections of the accelerometer during the activity in variouspositions inside the engineered environment such that it records motionassociated with one type of activity while excluding movementcharacteristic of another form of activity; (iii) applying a multiplierto the accelerometer deflections collected in (ii) to assign a weightedvalue indicative of the level of effort exerted during the activity;(iv) saving deflections from each type of movement such that deflectioncounts are segregated by activity type and determining the amount ofrelative energy expended by the user during any given time period in theactivity type; (v) transferring deflection counts and relative energyexpended to a device; and (vi) processing the deflection counts andrelative energy expended for display by the device; (c) instantaneouslyderiving, via a computing device, a calculated currently determinedconstant that reflects efficiency, which is a rate at which the userextracts energy from the food units that can be referenced againstpredicted and actual changes in weight, wherein the constant is asurrogate for intrinsic metabolic rate; (d) instantaneously calculatingby an algorithm from the calculated currently determined constant in (c)a predicted energy balance for the user, by:
 1. calculating a ratio ofan amount of activity units expected divided by an amount of activityobserved;
 2. calculating a ratio of an amount of food units expecteddivided by an amount of food units observed;
 3. weighting the ratio in(a) against the ratio in (b) according to goals of the user; and 4.modifying the weighted ratio in (3) by a rate at which the user performsthe activity/work (e) instantaneously predicting a change in weight fromthe predicted energy balance; and (f) determining fitness level of theuser based on the efficiency of energy consumption.
 2. The method ofclaim 1, wherein the programming independent of a magnetic field is bywireless transmission from a device.
 3. The method of claim 2, whereinthe wireless transmission is a Bluetooth™ signal.
 4. The method of claim2, wherein the device is selected from the group consisting of a smartcell phone, a computer and a tablet.
 5. The method of claim 4, whereinthe device is a smart cell phone.
 6. The method of claim 1, wherein theprogramming independent of a magnetic field is by buttons on an activitymodule comprising the programmable accelerometer.
 7. The method of claim1, wherein the change in weight is displayable either as a numericweight or as a colored dot display system.
 8. The method of claim 7,wherein the colored dot display system comprises: (a) a red dotrepresenting weight gain other than muscle; (b) a green dot representingmuscle growth or weight loss; and (c) a yellow dot representing nochange in fat/muscle ratios.
 9. The method of claim 1, wherein thedeflection counts in (d) are segregated by activity type in a processor.10. The method of claim 9, wherein the activity type is a generalactivity type.
 11. The method of claim 10, wherein the activity typeconsists of activity monitoring modes selected from the group consistingof a travel activity mode and a sleep activity mode.
 12. The method ofclaim 1, wherein the accelerometer is a triaxial accelerometer.
 13. Themethod of claim 1, wherein when the type of activity is sleep, themethod further comprises a method for measuring quality of sleepcomprising: (i) assigning a time period in which the user is going tobed; (ii) collecting deflections of the accelerometer during theassigned time period of (i); (iii) transferring the deflection countscollected in (ii) corresponding to sleep activity to a device; (iv)ending the time period assigned in (i); and (v) processing thedeflection counts for display by the device, wherein an increase inaccelerometer deflections recorded compared to an average ofaccelerometer deflections recorded is indicative of a sleep disorder.14. The method of claim 13, wherein the sleep disorder is selected fromthe group consisting of sleep apnea, insomnia and restless leg syndrome.15. The method of claim 14, wherein the sleep disorder is sleep apnea.16. The method of claim 7, wherein when the type of activity is sleep,the method further comprises a method for determining an increasedphysiological benefit during sleep comprising: (i) assigning a timeperiod in which the user is going to bed; (ii) collecting deflections ofthe accelerometer during the assigned time period of (i); (iii)transferring the deflection counts collected in (ii) corresponding tosleep activity to a device; (iv) ending the time period assigned in (i);and (v) processing the deflection counts for display by the device,wherein no change or a decrease in accelerometer deflections recordedcompared to an average of accelerometer deflections recorded isindicative of an increased physiological benefit during sleep.
 17. Themethod of claim 16, wherein the increased physiological benefit is anincrease in interstitial space in brain.
 18. The method of claim 16,wherein the increased physiological benefit is an increase in convectiveexchange of cerebrospinal fluid (CSF) and interstitial fluid (ISF) inbrain.
 19. The method of claim 16, wherein the increased physiologicalbenefit is an increased rate of clearance from brain of a protein linkedto neurodegenerative disease.
 20. The method of claim 19, wherein theprotein is selected from the group consisting of β-amyloid (Aβ),α-synuclein and tau.
 21. The method of claim 1, wherein the informationused to determine weight gain other than muscle, muscle growth or weightloss, or no change in fat/muscle ratios, is integrated into multipleparameters that form a health quotient displayed by the device as asingle point on a scale ranging from fit to healthy to unhealthy to atrisk.
 22. A method for instantaneously and continuously assessing realtime energy balance for fitness management comprising, in order: (a)collecting food intake information for actual or expected food intake ofa user over a specified period of time and contemporaneously convertingthe food intake information into food intake energy units for the firstperiod of time, wherein the food intake units are based on relativeenergy content of one food compared to another without relying onstandard caloric values; (b) collecting by a device activity informationfor actual or expected activity by the user over the specified period oftime and contemporaneously converting the activity information intoenergy units for the user for the first period of time, wherein thecollecting for actual activity is achieved by wireless transmission by amotion sensor and the motion sensor is a programmable accelerometer, thefunctional status of which is altered by: (i) at least one moveablemagnet encircling the programmable accelerometer; (ii) collectingdeflections of the accelerometer during the activity in variouspositions inside the engineered environment such that it records motionassociated with one type of activity while excluding movementcharacteristic of another form of activity; (iii) applying a multiplierto the accelerometer deflections collected in (ii) to assign a weightedvalue indicative of the level of effort exerted during the activity;(iv) saving deflections from each type of movement such that deflectioncounts are segregated by activity type and determining the amount ofrelative energy expended by the user during any given time period in theactivity type; (v) transferring deflection counts and relative energyexpended to a device; and (vi) processing the deflection counts andrelative energy expended for display by the device; (c) instantaneouslyderiving, via a computing device, a calculated currently determinedconstant that reflects efficiency, which is a rate at which the userextracts energy from the food units that can be referenced againstpredicted and actual changes in weight, wherein the constant is asurrogate for intrinsic metabolic rate; (d) instantaneously calculatingby an algorithm from the calculated currently determined constant in (c)a predicted energy balance for the user, by:
 1. calculating a ratio ofan amount of activity units expected divided by an amount of activityobserved;
 2. calculating a ratio of an amount of food units expecteddivided by an amount of food units observed;
 3. weighting the ratio in(a) against the ratio in (b) according to goals of the user; and 4.modifying the weighted ratio in (3) by a rate at which the user performsthe activity/work (e) instantaneously predicting a change in weight fromthe predicted energy balance; and (f) determining fitness level of theuser based on the efficiency of energy consumption.
 23. The method ofclaim 22, wherein the change in weight is displayable either as anumeric weight or as a colored dot display system.
 24. The method ofclaim 23, wherein the colored dot display system comprises: (a) a reddot representing weight gain other than muscle; (b) a green dotrepresenting muscle growth or weight loss; and (c) a yellow dotrepresenting no change in fat/muscle ratios.
 25. The method of claim 22,wherein the deflection counts in (iv) are segregated by activity type ina processor.
 26. The method of claim 22, wherein movement of the atleast one moveable magnet around the programmable accelerometerinitiates a programming change to alter the functional status of theaccelerometer into activity monitoring modes.
 27. The method of claim26, wherein the activity monitoring modes are selected from the groupconsisting of a standard mode (S), a running/jogging mode (A+), abicycle mode (A), a weight lifting/resistance training/yoga mode (W+),an aerobic-based gym equipment mode (W) and a sleet activity mode. 28.The method of claim 27, wherein the standard mode (S) comprises routinedaily activity.
 29. The method of claim 22, wherein the type of activityis selected from the group consisting of aerobic and non-aerobic. 30.The method of claim 29, wherein the aerobic activity is selected fromthe group consisting of walking, jogging, running, biking, tennis,basketball, soccer, circuit training and elliptical training.
 31. Themethod of claim 29, wherein the non-aerobic activity is selected fromthe group consisting of weight lifting, yoga, Pilates, and resistancetraining.
 32. The method of claim 22, wherein the accelerometer is atriaxial accelerometer.
 33. The method of claim 22, wherein the at leastone moveable magnet is a sphere.
 34. The method of claim 22, wherein theat least one moveable magnet is contained within at least one tube. 35.The method of claim 34, wherein the at least one tube is located withina means for attaching the accelerometer to a user.
 36. The method ofclaim 34, wherein the at least one tube is located within a casing of anactivity module.
 37. The method of claim 22, wherein when the type ofactivity is sleep, the method further comprises a method for measuringquality of sleep comprising: (i) assigning a time period in which theuser is going to bed; (ii) collecting deflections of the accelerometerduring the assigned time period of (i); (iii) transferring thedeflection counts collected in (ii) corresponding to sleep activity to adevice; (iv) ending the time period assigned in (i); and (v) processingthe deflection counts for display by the device, wherein an increase inaccelerometer deflections recorded compared to an average ofaccelerometer deflections recorded is indicative of a sleep disorder.38. The method of claim 37, wherein the sleep disorder is selected fromthe group consisting of sleep apnea, insomnia and restless leg syndrome.39. The method of claim 38, wherein the sleep disorder is sleep apnea.40. The method of claim 23, wherein when the type of activity is sleep,the method further comprises a method for determining an increasedphysiological benefit during sleep comprising: (i) assigning a timeperiod in which the user is going to bed; (ii) collecting deflections ofthe accelerometer during the assigned time period of (i); (iii)transferring the deflection counts collected in (ii) corresponding tosleep activity to a device; (iv) ending the time period assigned in (i);and (v) processing the deflection counts for display by the device,wherein no change or a decrease in accelerometer deflections recordedcompared to an average of accelerometer deflections recorded isindicative of an increased physiological benefit during sleep.
 41. Themethod of claim 40, wherein the increased physiological benefit is anincrease in interstitial space in brain.
 42. The method of claim 40,wherein the increased physiological benefit is an increase in convectiveexchange of cerebrospinal fluid (CSF) and interstitial fluid (ISF) inbrain.
 43. The method of claim 40, wherein the increased physiologicalbenefit is an increased rate of clearance from brain of a protein linkedto neurodegenerative disease.
 44. The method of claim 43, wherein theprotein is selected from the group consisting of β-amyloid (Aβ),α-synuclein and tau.
 45. The method of claim 22, wherein the informationused to determine weight gain other than muscle, muscle growth or weightloss, or no change in fat/muscle ratios, is integrated into multipleparameters that form a health quotient displayed by the device as asingle point on a scale ranging from fit to healthy to unhealthy to atrisk.